Series 2, Number 138 March 2005

Statistical Methodology of 

the National Immunization 

Survey, 1994–2002 
Copyright information 

All material appearing in this report is in the public domain and may be 

reproduced or copied without permission; citation as to source, however, is 

appreciated. 

Suggested citation 

Smith PJ, Hoaglin DC, Battaglia MP, et al. Statistical methodology of the 

National Immunization Survey, 1994–2002. National Center for Health Statistics. 

Vital Health Stat 2(138). 2005. 

Library of Congress Cataloging-in-Publication Data 

Statistical methodology of the National immunization survey, 1994–2002 / Philip 

J. Smith ... [et al.]. 

p. ; cm. — (Vital and health statistics. Series 2, Data evaluation and 

methods research ; no. 138) (DHHS publication ; no. (PHS) 2005–1338) 

Includes bibliographical references. 

ISBN 0-8406-0596-X 

1. National immunization survey. 2. Immunization of children— 

United States—Statistical methods. 3. Immunization of infants— 

United States—Statistical methods. 4. Medical statistics—Methodology. 

[DNLM: 1. Mass Immunization—Child—United States. 2. Mass Immunization— 

Infant—United States. 3. Health Surveys—United States. 4. Statistics— 

methods—United States. WS 135 S797 2005] 

I. Smith, Philip J. (Philip James), 1951- II. National Center for Health Statistics 

(U.S.) III. Series. IV. Series: DHHS publication ; no. (PHS) 2005–1338 

RA409 .U45 no. 138 [RJ240] 

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Printed on acid-free paper. 
Series 2, Number 138 

Statistical Methodology of the 

National Immunization Survey, 

1994–2002 

Data Evaluation and Methods 

Research 

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES 

Centers for Disease Control and Prevention 

National Center for Health Statistics 

Hyattsville, Maryland 

March 2005 

DHHS Publication No. (PHS) 2005-1338 
National Center for Health Statistics 

Edward J. Sondik, Ph.D., Director 

Jack R. Anderson, Deputy Director 

Jennifer H. Madans, Ph.D., Associate Director for Science 

Lawrence H. Cox, Ph.D., Associate Director for Research 

and Methodology

Edward L. Hunter, Associate Director for Planning, Budget,

and Legislation

Michael H. Sadagursky, Associate Director for

Management and Operations

Margot A. Palmer, Director for Information Technology

Phillip R. Beattie, Director for Information Services

Diane M. Makuc, Dr.P.H., Acting Associate Director for

Analysis and Epidemiology

Charles J. Rothwell, Director for Vital Statistics

Jane E. Sisk, Ph.D., Director for Health Care Statistics

Jane F. Gentleman, Ph.D., Director for Health Interview

Statistics

Clifford L. Johnson, Director for Health and Nutrition

Examination Surveys

Office of Research and Methodogy 

Lawrence H. Cox, Ph.D., Associate Director 

Kenneth M. Harris, Acting Chief, Interdisciplinary Research 

Center and Laboratories 

P. Douglas Williams, Acting Chief, Statistical Research and 

Survey Design Staff 
Contents

Introduction ............................................................................................. 1

Background and Outline ................................................................................... 2

Sampling Design, Questionnaires, and Response Rates ........................................................... 2

The NIS Sampling Design ................................................................................ 2

The 2002 RDD Survey .................................................................................. 3

The 2002 Immunization History Questionnaire (IHQ) and Provider Survey ........................................ 4

Response Rates and Key Monitoring Statistics, 1994–2002 ..................................................... 4

Coverage of the Target Population, 2002 .................................................................... 7

Characteristics of Children in the NIS Sample, 2002 .......................................................... 8

Estimation Methodology ................................................................................... 8

1994–97 Estimation Methodology .......................................................................... 8

1998–2001 Estimation Methodology ........................................................................ 10

2002 Estimation Methodology ............................................................................. 14

Evaluation of the Effect of Incomplete Ascertainment of Provider-reported Vaccination Histories on Estimates of

Vaccination Coverage ................................................................................... 21

The First Three Topical Modules, 2001 ....................................................................... 25

Analytic Objectives ..................................................................................... 27

The Design for the First Three Topical Modules .............................................................. 28

Weighting Methodology for Topical Modules (Q3/2001–Q2/2002) ................................................ 29

Two Additional Quarters of Topical Modules ................................................................. 32

Future Topical Modules................................................................................... 32

Public-Use Files........................................................................................... 32

Summary ................................................................................................ 33

References ............................................................................................... 34

Appendix ................................................................................................ 53

National Immunization Survey Immunization History Questionnaire .............................................. 53

Text Tables 

A. Content of the household interview questionnaire: National Immunization Survey, 2002 ......................... 3

B. Strata based on household’s report of child’s 4:3:1:3 up-to-date status and household’s use of shot card, percentage

distribution of children by stratum, and percentage of children in each stratum who are 4:3:1:3 up to date in

providers’ reports: National Immunization Survey, 1997 ................................................... 10

C. Variables used in the model selection for the response propensity model: National Immunization Survey, 2002 ...... 12

D. Variables used for raking the response-propensity-adjusted sampling weights of children with provider data:

National Immunization Survey, 2002 ................................................................... 13

E. Notation for numbers in the target population at the time of the telephone survey by the combination of telephone

status and interruption status ......................................................................... 17

F. Instructions for downloading Current Population Survey monthly survey data files .............................. 18

G. Effect on estimated 4:3:1:3 coverage of a modification of the 1998–2001 estimation methodology that only

accounted for children with no vaccine doses: National Immunization Survey, 1995–2002 ....................... 21

H. Estimated 4:3:1:3 coverage by provider-reported ascertainment status, among children with adequate provider data

and two or more providers: National Immunization Survey, 1995–2002 ....................................... 21

J. Expected 95-percent confidence interval half-widths for topical modules designed to yield national coverage

estimates within subdomains of specified size ............................................................ 29

iii 
K. State sample sizes and expected 95-percent confidence interval half-widths for the health insurance module ......... 29

L. Key indicators for the topical modules: National Immunization Survey, third quarter of 2001 through second quarter

of 2002 ........................................................................................... 30

M. Logistic regression predictors for randomization to a topical module: National Immunization Survey, third quarter of

2001 through second quarter of 2002 ................................................................... 30

N. Logistic regression models for predicting presence of adequate provider data: National Immunization Survey, third

quarter of 2001 through second quarter of 2002 .......................................................... 31

O. Key indicators for the topical modules: National Immunization Survey, third quarter of 2001 through fourth quarter

of 2002 ........................................................................................... 32

Detailed Tables 

1. Number of children 19–35 months of age, by State and immunization action plan area: United States, 2002 ......... 36

2. Response rates and key monitoring statistics: National Immunization Survey, 1994–2002 ........................ 37

3. Factors associated with having two or more vaccination providers, among sampled children with adequate provider

data: National Immunization Survey, 2002 .............................................................. 38

4. Characteristics associated with incomplete ascertainment, among sampled children with two or more vaccination

providers and adequate provider data: National Immunization Survey, 2002 ................................... 39

5. Response at successive stages of data collection: National Immunization Survey, 2002 .......................... 41

6. Child, maternal, and household characteristics of children with a completed random-digit-dialed interview and

children who had adequate provider data: National Immunization Survey, 2002 ................................ 43

7. Estimated percentage of children 2 years of age residing in telephone households by immunization action plan area:

United States, 1996–97 and 2000 ...................................................................... 44

8. Number of sample children by each combination of the three characteristics that define poststratification cells, with

poststratification cells produced by the collapsing procedure: Massachusetts—City of Boston, second, third, and

fourth quarters of 1994 .............................................................................. 45

9. Prevalence of selected characteristics by the combination of household telephone status at the time of the survey and

interruption in telephone service: Nine large States, 1997–99 ............................................... 46

10. Calculations for applying the interruption-based adjustment: Georgia–Rest of State immunization action plan area,

1996–97 ........................................................................................... 47

11. Vaccination coverage rates revised to account for children with no vaccinations and incorporating new nontelephone

adjustment by State: National Immunization Survey, 2001 ................................................. 48

12. Differences in estimates of 4:3:1:3 vaccination coverage produced by using the new nontelephone adjustment and

accounting for children with no vaccinations by State: National Immunization Survey, 2001 ...................... 50

13. Percentage of sampled children with adequate provider data who were incompletely ascertained by race/ethnicity:

National Immunization Survey, 1995–2002 .............................................................. 51

14. State and national estimates of 4:3:1:3:3 vaccination coverage for the 2002 estimation methodology and the three

alternative methodologies: National Immunization Survey, 2002 ............................................. 52

Figures 

1. Trends in key indicators from household and provider data collection: National Immunization Survey, 1994–2002 .... 5

2. Percentage of sampled children with two or more providers and with some providers not reporting among children

with two or more providers: National Immunization Survey, 1995–2002 ...................................... 7

3. Plot of estimated difference in vaccination coverage between alternative methodology #1 and the 2002 estimation

methodology versus the 4:3:1:3:3 estimates obtained from the 2002 estimation methodology: National Immunization

Survey, 2002 ...................................................................................... 23

4. Plot of estimated difference in vaccination coverage between alternative methodology #2 and the 2002 estimation

methodology versus the 4:3:1:3:3 estimates obtained from the 2002 method: National Immunization Survey, 2002 .... 24

5. Plot of estimated difference in vaccination coverage between alternative methodology #3 and the 2002 estimation

methodology versus the 4:3:1:3:3 estimates obtained from the 2002 method: National Immunization Survey, 2002 .... 25

6. Percentage of incompletely ascertained children whose parent reported vaccination histories using a shot card by

State: National Immunization Survey, 2002 .............................................................. 26

7. Difference between the 2002 methodology and estimation method #3 versus the percentage of incompletely ascertained

children in the sample who had a shot card from which household-reported vaccination histories were obtained during

the National Immunization Survey random-digit-dialed interview: National Immunization Survey, 2002 ............. 27

iv 
Objectives 

Methods 

(DCM). 

Results 

DCM. 

Keywords: c 

c randomc 

Since 1994 the National Immunization 

Survey (NIS) has monitored progress 

toward the Healthy People 2000 and 2010 

vaccination goals. The NIS collects data 

in two phases: first, a random-digit-dialing 

(RDD) telephone survey to identify 

households with children 19–35 months 

old and, second, a mail survey to 

vaccination providers to obtain vaccination 

histories used to estimate vaccination 

coverage rates. This report reviews the 

methodologies used in the 1994–2002 

NIS to obtain official estimates of 

vaccination coverage and describes the 

methodology used for the first three 

topical modules of the NIS. 

From 1994 to 1997 the NIS used a 

variation of a two-phase estimator to 

compensate for missing provider-reported 

vaccination histories. Between 1998 and 

2001 a weighting-class estimator was 

used. In 2002 and thereafter the 

weighting-class approach was refined to 

account for households that do not have 

telephones and for unvaccinated children. 

To collect data on immunization-related 

topics, the NIS sample was randomized 

among three topical modules: health 

insurance and ability to pay for 

vaccinations (HIM); parental knowledge 

and experiences about vaccinations 

(PKM); and daycare attendance, 

breastfeeding practices, and participation 

in the Special Supplemental Nutrition 

Program for Women, Infants, and Children 

In 2001 among children with 

completed RDD interviews, 0.3 percent 

were entirely unvaccinated. Together, the 

new nontelephone adjustment and the 

refinement for unvaccinated children 

yielded revised estimates that were within 

1.5 percentage points of the original 

estimates obtained using the 1998–2001 

methodology. Over the six quarters during 

which the first three topical modules were 

fielded (from mid-2001 through 2002), 

21,163 children were randomized to the 

HIM, 3,576 to the PKM, and 3,511 to the 

Missing at random 

nontelephone adjustment 

digit dialing split sampling 

Statistical Methodology of the 

National Immunization Survey, 

1994–2002 

by Philip J. Smith, Ph.D., Centers for Disease Control and 

Prevention; David C. Hoaglin, Ph.D., and Michael P. Battaglia, M.A., 

Abt Associates Inc.; Meena Khare, M.S., National Center for Health 

Statistics; and Lawrence E. Barker, Ph.D., Centers for Disease Control 

and Prevention 

Introduction 

I

n 1994 the Childhood Immunization 

Initiative (CII) was established 

to: 

+ Improve the delivery of vaccines to 

children. 

+ Reduce the cost of vaccines for 

parents. 

+ Enhance awareness, partnerships, 

and community participation. 

+ Improve vaccinations and their use. 

+ Monitor vaccination coverage and 

occurrences of disease (1). 

Subsequently, the Healthy People 

2000 and 2010 objectives established 

the goal of having at least 90 percent of 

2-year-old children fully vaccinated with 

the recommended schedule of 

vaccines (2,3). To fulfill the CII mandate 

of monitoring vaccination coverage and 

marking progress toward achieving the 

Healthy People 2000 and 2010 goals, 

the National Immunization Survey (NIS) 

has been implemented by the National 

Immunization Program (NIP) and the 

National Center for Health Statistics 

(NCHS), Centers for Disease Control 

and Prevention (CDC). The data 

collection contractor has been Abt 

Associates Inc. 

The target population is children 

between 19 and 35 months of age living 

in households in the United States at the 

time of the interview. Official NIS 

coverage estimates give rates of being 

up-to-date (UTD) with respect to the 

recommended numbers of doses of 

seven vaccines: diphtheria and tetanus 

toxoids and pertussis vaccine (DTP or 

DTaP, where aP refers to acellular 

pertussis vaccine), 4 doses; Haemophilus 

influenzae type b vaccine (Hib), 3 doses; 

poliovirus vaccine (polio), 3 doses; 

measles-containing vaccine (MCV), 

1 dose; hepatitis B vaccine (Hep B), 

3 doses; varicella vaccine (VRC), 

1 dose; and pneumococcal conjugate 

vaccine (PCV), 3 doses (4). (In October 

2000 the Advisory Committee on 

Immunization Practices recommended 

that all children 2–23 months of age 

receive 4 doses of pneumococcal 

vaccine. The pneumococcal vaccine is 

relatively new; there was a supply 

problem, and a catch-up schedule 

provided for some children to be fully 

compliant despite having received fewer 

than 4 doses. On February 13, 2004, 

CDC recommended that health care 

providers temporarily suspend routine 

use of the fourth dose of 7-valent 

pneumococcal conjugate vaccine 

(PCV7) when immunizing healthy 

children (5).) 

The authors gratefully acknowledge the assistance of the following members of the NCHS Information 

Design and Publishing Staff, Office of Information Services: Kathy J. Sedgwick, for her careful review and 

editing of the final report; Zung T. N. Le, who typeset the report; and Jarmila Gail Ogburn, who prepared 

the graphics. 

Page 1 
Page 2 [ Series 2, No. 138 

Vaccination coverage estimates are 

published for each calendar year. The 

time lag between the end of a reporting 

period and publication of official 

estimates is approximately 6 months. 

Beginning with the second quarter 

of 1994 (Q2/1994), the NIS has 

conducted quarterly surveys in 78 

Immunization Action Plan (IAP) areas, 

consisting of the 50 States, the District 

of Columbia, and 27 other large urban 

areas (table 1). This design has made it 

possible to produce annualized estimates 

of vaccination coverage levels within 

each of the 78 IAP areas with an 

acceptable degree of precision. Further, 

by using the same data collection 

methodology and survey questionnaires 

in all IAP areas, the NIS produces 

estimates that are comparable among 

IAP areas and over time. 

In addition to providing vaccination 

data from which coverage rates may 

be monitored, the objectives of the 

NIS are to assist CDC in allocating 

resources to States for the purpose of 

increasing coverage rates, to identify 

subpopulations and/or geographic 

areas in which rates are low, and to 

provide a database for epidemiologic 

research. 

Background and 

Outline 

Since its inception in 1994 the NIS 

methodology has undergone 

several noteworthy revisions. This 

report documents these revisions as they 

were implemented between 1994 and 

2002. As a foundation for subsequent 

sections, ‘‘Sampling Design, 

Questionnaires, and Response Rates’’ 

presents a synopsis of the NIS sampling 

design, describes the content of the 

survey questionnaires used in 2002, and 

reviews response rates and key 

monitoring statistics. 

‘‘Estimation Methodology’’ 

describes how the NIS methodology for 

estimating vaccination coverage rates 

changed between 1994 and 2002. The 

original methodology, used between 

1994 and 1997, was based on a 

modification of the two-phase sampling 

estimator. The methodology introduced 

in 1998 uses a weighting-class 

estimator, and modifications introduced 

in 2002 account more accurately for 

children living in households with no 

telephones and for children who have 

had no vaccinations. 

‘‘The First Three Topical Modules, 

2001’’ describes the objectives and 

design of the first three topical modules, 

incorporated in the NIS to collect 

additional information for improving 

vaccination coverage. These modules 

focused on the relationship between 

vaccination status and families’ ability 

to pay for vaccinations; on parental 

knowledge about vaccinations; and on 

daycare attendance, participation in the 

U.S. Department of Agriculture’s 

Special Supplemental Nutrition Program 

for Women, Infants, and Children 

(WIC), and breastfeeding practices. The 

split-sampling design for the modules is 

described, along with the statistical 

methodology used to obtain sampling 

weights for children who completed the 

household interview, completed a topical 

module, and had a sufficiently detailed 

vaccination history reported by their 

vaccination providers to evaluate their 

vaccination status. 

‘‘Public-Use Files’’ gives a brief 

description of the NIS public-use data 

files and supporting documentation. 

Sampling Design, 

Questionnaires, and 

Response Rates 

The NIS Sampling Design 

The NIS uses two phases of data 

collection to obtain vaccination 

information for a large national 

probability sample of young children: a 

random-digit-dialing (RDD) survey 

designed to identify households with 

children between 19 and 35 months of 

age, followed by the NIS Provider 

Record Check (PRC) survey, which 

obtains provider-reported vaccination 

histories for these children. Data from 

the PRC yield each child’s number of 

doses for each of the seven vaccines. 

These counts are then compared with 

the number of doses recommended by 

the vaccination schedule to determine 

whether the child is UTD. These data, 

along with sampling weights and NIS 

survey design information, are used to 

obtain estimated vaccination coverage 

rates. 

This section summarizes these two 

phases of data collection. Other 

descriptions of the sample design are 

given by Smith et al., Ezzati-Rice et al., 

and Zell et al. (6–8). 

The 2002 RDD Sample 

The RDD sampling phase uses 

independent quarterly samples of 

telephone numbers in each of the 78 

IAP areas. Table 1 lists the 78 IAP areas 

and shows the number of children 

19–35 months of age in each IAP area 

and State in 2002. A total of 31,693 

households completed the RDD 

interview for children between 19 and 

35 months of age in 2002, an average of 

406 per IAP area. The procedures for 

managing the quarterly RDD samples 

ensure that the interviews in each IAP 

area are spread evenly across the year. 

The main goals of the RDD 

sampling phase are to: 

+ Select a probability sample of 

telephone numbers for each IAP area. 

+ Ensure that the desired sample size 

of children with completed 

interviews is achieved in each IAP 

area. 

+ Minimize in a cost-effective manner 

the number of age-eligible children 

excluded from the sampling frame. 

+ Maintain an up-to-date sampling 

frame of telephone numbers. 

To accomplish these goals the NIS 

uses the list-assisted method of 

RDD (9). This method selects a random 

sample of telephone numbers from 

banks of 100 consecutive telephone 

numbers (e.g., 617–495–0000 to 

617–495–0099) that contain one or more 

directory-listed residential telephone 

numbers (the 1+ working banks). The 

sampling frame of telephone numbers is 

updated each quarter to include new 

banks. Although the number of cellular 

telephone users in the United States has 

increased rapidly, most households 
continue to maintain wire line telephone 

service. Also, most cellular telephone 

users pay for incoming calls. Therefore, 

cellular telephone exchanges are 

currently excluded from the NIS 

sampling frame. 

Within each IAP area the RDD 

sample is randomly segmented into 

replicates to allow for carefully 

controlled release of the sample. Some 

RDD surveys give all sampled telephone 

numbers to interviewers for dialing. 

Because over one-half of selected 

numbers are business or unassigned, the 

NIS uses an automated screening 

procedure to remove a portion of these 

unproductive telephone numbers from 

the sample before interviewer dialing 

begins. 

The NIS Provider Record 

Check Survey 

At the end of the RDD interview, 

consent to contact the child’s 

vaccination providers is requested from 

the parent or guardian. When verbal 

consent is obtained, those providers are 

mailed an immunization history 

questionnaire (IHQ), which asks them to 

record the child’s vaccination history. 

The data from these IHQs are entered, 

cleaned, edited, and merged to produce 

a child-level record. 

The 2002 RDD Survey 

The computer-assisted telephone 

interview (CATI) questionnaire used in 

the RDD portion of data collection 

includes a screening section to identify 

households with children in the age 

range 19–35 months and a vaccination 

interview based on the Immunization 

Supplement of the National Health 

Interview Survey (NHIS) (10). The NIS 

CATI questionnaire has been translated 

into Spanish, and Language Line 

Services (formerly part of AT&T) is 

used for real-time translation of 

the interview into many other 

languages (11,12). People who are deaf, 

hard of hearing, or speech-impaired are 

included in NIS interviews by using text 

telephone (TTY). When a number is 

dialed and the TTY tone is encountered, 

the number is put in a separate queue 

for handling by a specialist with access 

Series 2, No. 138 [ Page 3 

Table A. Content of the household interview questionnaire: National Immunization Survey, 

2002 

Section Content 

S Screening questions to determine eligibility, roster of eligible children, availability of shot 

records 

MR Most-knowledgeable-respondent callback questions 

A Vaccination history, asked if shot records are available 

B Vaccination history, asked if shot records are not available 

C Demographic and socioeconomic questions 

D Provider information and request for consent to contact the eligible child’s vaccination 

providers 

to the TTY equipment needed to 

communicate with the household. 

Table A summarizes the content of each 

section of the 2002 NIS household 

interview questionnaire. 

In ‘‘Section S’’ the reason for the 

telephone call and the purpose of the 

survey are explained to the respondent, 

and the household is screened to 

determine whether it contains any 

children between 19 and 35 months of 

age. In 2002 TTY was used to complete 

‘‘Section S’’ for 23 households. 

In ‘‘Section MR,’’ if the household 

has an eligible child, the respondent is 

asked whether he or she is the most 

knowledgeable person about the child’s 

vaccination history. If the respondent 

indicates that another person in the 

household is the most knowledgeable and 

that person is unavailable, a callback is 

scheduled to interview the most 

knowledgeable person at a later date. 

When information from the child’s 

vaccination record (shot card) is 

available during the interview, the 

respondent is asked to provide that 

information in ‘‘Section A.’’ When shot 

card information is not available, the 

respondent is asked to recall from 

memory information about the child’s 

vaccination history in ‘‘Section B.’’ 

‘‘Section C’’ obtains information 

that includes the relationship of the 

respondent to the child, Hispanic 

ethnicity of the child, the race of the 

child, Hispanic ethnicity of the mother, 

the race of the mother, information 

about household income and educational 

attainment of the mother, and other 

information on the socioeconomic 

characteristics of the household and its 

eligible children. 

At the conclusion of the RDD 

interview (in ‘‘Section D’’), consent is 

requested to contact the child’s 

vaccination providers. If verbal consent 

is obtained, identifying information 

(name, address, and telephone number) 

on the vaccination provider(s) is 

requested. When verbal consent and 

sufficient identifying information are 

obtained, the IHQ is mailed to the 

child’s vaccination provider(s), along 

with a copy of a form documenting the 

household’s consent. 

The protocol for the 2002 RDD 

survey used the following primary rules 

for discontinuing call attempts to sample 

telephone numbers: 

+ A maximum of 10 call attempts were 

made to ring-no-answer numbers. 

+ A maximum of 15 call attempts 

were made to numbers that resulted 

in a residential or potentially 

residential answering-machine 

message. 

+ A maximum of 25 call attempts 

were made to likely and known 

households. 

+ Hostile refusals received no 

additional call attempts. 

+ Requests to be placed on the ‘‘do 

not call list’’ received no additional 

call attempts. 

+ A verbal refusal on two call 

attempts resulted in no further 

attempt. 

+ A hangup during the introduction on 

three call attempts resulted in no 

further attempts. 

Major changes from 1994 to 2002 

in the protocol of the RDD survey 

include: 

+ Discontinuing after 1996 the 

practice of calling local telephone 

company business offices in an 

effort to determine whether 

unresolved telephone numbers were 

residential numbers. 
Page 4 [ Series 2, No. 138 

+ Introducing in 1996 a provider name 

and address database to allow 

interviewers to determine the 

complete address of a provider 

identified by a respondent. 

+ Reducing in 1999 call attempts for 

ring-no-answer telephone numbers 

from 24 to 15. 

+ Introducing in 2000 an improved 

method of prescreening the sample 

to remove a portion of the 

nonworking and business telephone 

numbers. 

+ Introducing in 2000 a more 

comprehensive database for advance 

letter mailing. 

+ Reducing in 2000 call attempts for 

numbers that resulted in a residential 

or potentially residential answeringmachine message from 24 to 15. 

+ Introducing in 2001 a provider 

database that allowed interviewers to 

view all providers in a ZIP Code 

area. 

+ Eliminating in 2001 callbacks to 

households that did not have their 

shot card available at the time of the 

interview. (The interview was 

completed using respondent recall.) 

+ Reducing in 2002 call attempts for 

ring-no-answer numbers from 15 to 

10. 

+ Sending refusal conversion letters in 

2002 to respondents who refused to 

give consent for contacting 

vaccination providers. 

The 2002 Immunization 

History Questionnaire 

(IHQ) and Provider Survey 

The IHQ is designed to be simple 

and brief, to minimize burden on the 

providers, and to encourage participation 

in the survey. Between 1994 and 

Q2/2002, a 2-page IHQ was used. 

During Q3/2002, a new, 4-page IHQ 

(see ‘‘Appendix I’’) was introduced. 

The first page includes space for a label 

that contains identifying information 

about the child (child’s name and birth 

date and the full name of the parent). It 

also asks questions about the facility to 

which the IHQ was mailed: the types of 

care the facility provides; whether it is a 

federally qualified health center, a 

hospital-based clinic, a private practice, 

a public health department-operated 

clinic, a military health care facility, or 

a clinic associated with the WIC 

program; whether the facility is a 

Vaccines for Children (VFC) provider; 

and whether the facility reported any of 

the child’s immunizations to a 

community or State immunization 

registry. 

The second page of the IHQ 

provides instructions for completing the 

shot grid on the third page, which asks 

for the date on which each vaccination 

was administered as well as additional 

information about combinations of 

vaccines that were administered. The 

fourth page lists sources of further 

information about the NIP and vaccine 

recommendations and sources of data 

and statistics from previous years of the 

NIS. The page also gives a telephone 

number and an e-mail address and 

warns against sending confidential 

information about the child via e-mail. 

The data collection process aims to 

maximize response. Each provider may 

receive up to three separate mailings 

and a telephone call. The initial mailing 

consists of a cover letter from the NIP 

Director briefly describing the study and 

its goals, a copy of a Morbidity and 

Mortality Weekly Report article 

supplying national estimates from the 

NIS, a signed consent form, an IHQ, 

and a business reply envelope. 

Two weeks later postcards are sent 

to providers regardless of whether they 

have responded. The postcards serve to 

thank those who have responded and to 

remind those who have not. 

Five weeks after the initial mailing 

reminder mailings are sent to nonresponding providers. The reminder 

mailing includes: a cover letter asking 

the provider to complete the immunization information for the child listed on 

the questionnaire, an IHQ, and a 

business reply envelope. 

Seven weeks after the original 

mailing the remaining nonrespondents 

are prompted by telephone. Generally, 

these prompting calls serve to remind 

providers to return the completed 

questionnaires and include an offer to 

mail or fax new materials to those 

providers who request them. In some 

cases the questionnaire is completed by 

telephone. 

This approach emphasizes 

prompting providers as inexpensively 

and easily as possible at each stage. The 

most expensive and labor-intensive steps 

are reserved for the least responsive 

providers. 

IHQs that arrive by approximately 

3 weeks after the last prompting are 

included in that quarter ’s data file and 

in the data file for the 4-quarter period 

ending with that quarter. Any IHQs that 

arrive after this 3-week cutoff are 

included in the next 4-quarter file. 

The effort to collect vaccination 

histories has three main limitations. 

First, if the household respondent 

refuses to give consent to contact the 

child’s providers, the approved protocol 

allows only one attempt at refusal 

conversion. Second, some providers 

have indicated that they will not comply 

with any requests from the NIS and, 

therefore, are no longer sent any IHQs. 

Third, the field period for provider data 

collection must be limited to allow for 

timely release of vaccination coverage 

estimates. This constraint precludes 

additional reminder calls to 

nonresponding providers. 

Response Rates and Key 

Monitoring Statistics, 

1994–2002 

The NIS is one of the largest 

federally-sponsored telephone surveys. 

Among large national telephone surveys, 

it has a high response rate. This section 

describes the statistics and response 

rates that are monitored regularly to 

maintain a high level of response. 

Response Rates and Key 

Monitoring Statistics for 2002 

Several indicators of survey 

progress and data quality are routinely 

produced for each IAP area and at the 

national level. Statistics such as survey 

response rates also reflect data quality. 

Table 2 presents the key national 

monitoring indicators for NIS data 

collection from 1994 through 2002. 

The size and growth of the NIS are 

evidenced by the numbers listed in 

table 2. In 2002 2,055,371 telephone 

numbers (row 3) were called to meet the 
Series 2, No. 138 [ Page 5 

objective of obtaining estimates of 

vaccination coverage with predefined 

accuracy within each IAP area. Among 

the identified households 986,203 

(row 8) did not contain an age-eligible 

child, and 34,201 (3.4 percent, row 9) 

contained one or more age-eligible 

children. Among the households 

containing one or more age-eligible 

children, 30,974 (90.6 percent, row 10) 

completed the household RDD 

interview. A standard approach for 

measuring response in RDD surveys, 

known as the CASRO response rate, has 

been defined by the Council of American 

Survey Research Organizations (13). In 

2002 the CASRO (household) response 

rate (row 11) was 74.2 percent. The 

CASRO response rate can be calculated 

as the product of the resolution rate 

(84.8 percent, row 5), the screening 

completion rate (96.6 percent, row 7), 

and the interview completion rate 

among eligible households (90.6 percent, 

row 10). The resolution rate is the 

percentage of the total telephone 

numbers called that were classifiable as 

either nonworking, nonresidential, or 

residential. The screening completion 

rate is the percentage of known 

households that are successfully 

screened for the presence of age-eligible 

children. The interview completion rate 

is the percentage of households with one 

or more age-eligible children that 

complete the RDD interview. Alternative 

response rates that take into account 

both nonresponse and noncoverage are 

also used to monitor the NIS (8,14). 

Row 12 of table 2 shows that 

31,693 age-eligible children had 

completed RDD interviews in 2002. 

Rows 13–16 list monitoring indicators 

for the PRC phase. Specifically, row 13 

gives the rate of obtaining consent from 

household respondents to contact their 

children’s vaccination providers, 

86.7 percent in 2002. The number of 

IHQs that were mailed to vaccination 

providers was 34,444 (row 14). This 

number exceeds the number of children 

with consent because some children had 

more than one vaccination provider (on 

average, 1.37 per child). In 2002 among 

the children with completed NIS 

household RDD interviews, 21,410 

(67.6 percent, row 16) had adequate 

vaccination histories returned by their 

Figure 1. Trends in key indicators from household and provider data collection: National 

Immunization Survey, 1994–2002 

vaccination provider(s). (As discussed in 

‘‘Adjustment for Partial Nonresponse,’’ 

as of 2002 this total included children 

who have received no vaccinations.) 

Trends in Response Rates and 

Key Monitoring Statistics, 

1994–2002 

Trends in the CASRO response 

rate—Figure 1 displays the key 

response-rate indicators over the 9-year 

period from 1994 through 2002. For the 

first 3 years the CASRO response rate 

(row 11 of table 2) was at 85.8 percent 

or higher. From 1997 to 2002 it declined 

from 84.6 percent to 74.2 percent 

(12.6 percentage points lower than in 

1994). To understand the slow decline in 

the CASRO response rate, it is necessary 

to examine trends in the three component 

rates that make up the CASRO rate: the 

resolution rate, the screening completion 

rate, and the interview completion rate. 

The resolution rate (row 5) has 

shown a substantial decline over time 

and accounts for much of the decline in 

the CASRO response rate. The 

resolution rate was 94.3 percent or 

higher in the first 3 years of the NIS. 

These very high rates were due in part 

to the practice of calling local telephone 

company business offices in an effort to 

determine whether the unresolved 

telephone numbers (e.g., noncontact 

numbers) were residential numbers. This 

practice was discontinued after 1996 

because it did not yield a sufficient 

number of interviews with eligible 

households to make it cost-effective. 

From 1997 to 1999 the resolution rate 

declined from 92.1 percent to 

88.6 percent. The resolution rate held at 

88.1 percent in 2000. This was due to 

the introduction of an improved method 

of prescreening the RDD sample to 

remove a portion of the nonworking and 

business telephone numbers (row 2). In 

2001 the resolution rate declined to 

86.8 percent, and in 2002 it was 

84.8 percent. The decline in the 

resolution rate is consistent with the 

experience of other RDD surveys; more 

sample telephone numbers end up as 

unresolved (e.g., ring-no-answer to all 

call attempts). 

The screening completion rate 

(row 7) remained almost unchanged over 

the 9-year period. The lowest rate was 

96.0 percent in 2000, and the highest 

rate was 97.9 percent in 1997. The high 

rate reflects the ability of the interviewers to complete the eligibility 

screening questions with households 

identified in the RDD sample. 

The interview completion rate (row 

10) declined by 4.8 percentage points 

over the 9-year period. The rate in 1994 

was 95.4 percent. The rate declined 

gradually from 94.0 percent in 1996 to 
Page 6 [ Series 2, No. 138 

93.1 percent in 2000, 91.1 percent in 

2001, and 90.6 percent in 2002. The 

high interview completion rate reflects 

the interviewers’ continued success at 

completing the interview once an 

eligible household is identified. 

Trends in the number of advance 

letters mailed—The NIS mails advance 

letters to sample telephone numbers for 

which it can obtain addresses using a 

reverse-match procedure. Through 1999 

about 33 percent of the sample 

telephone numbers called were sent an 

advance letter; in 2000 a more 

comprehensive database increased the 

match rate to around 60 percent (row 4). 

The use of an advance letter has been 

shown to increase the overall response 

rate in the NIS (15), and greater use of 

the advance letter likely contributed to 

maintaining the high interview and 

screener completion rates that the NIS 

has continued to experience. 

Trends in the percentage of children 

with adequate provider data—The 

conduct of the provider survey has 

changed in important ways, as reflected 

in the percentage of children with 

adequate provider data (row 16). In 

1995 this was only 50.6 percent. In 

1996 the use of follow-up procedures 

for providers who had not returned their 

IHQs raised it to 63.4 percent. In 1997 a 

tracking system for provider surveys 

was implemented, and the percentage of 

children with adequate provider data 

rose to 69.7 percent. From 1998 to 2002 

the percentage ranged between 

65 percent and 70 percent, and it showed 

no pattern of decline. Thus, although the 

CASRO response rate has declined over 

time, the product of the CASRO 

response rate and the percentage of 

children with adequate provider data (a 

measure of the overall success of the 

NIS in obtaining vaccination data for 

age-eligible children) is higher in 2002 

than it was in 1995. 

Potential limitations of adequate 

provider data: incompletely ascertained 

provider-reported vaccination 

histories—The NIS goes to considerable 

lengths to identify, for use in estimation, 

children whose provider-reported 

vaccination data are sufficient to 

determine their vaccination status. Even 

for such children, however, the 

vaccination history may not be 

complete. As a result, estimates of 

vaccination coverage are likely to be 

lower than the true level of coverage. 

The paragraphs that follow define the 

term ‘‘adequate provider data’’ and 

explore factors that may affect the 

completeness of children’s providerreported vaccination histories. 

Children with adequate provider 

data include those for whom all 

vaccination providers identified by the 

household responded to the IHQ. In 

addition, if some but not all identified 

providers responded, a set of rules 

determines whether the child is 

considered to have adequate provider 

data. These rules are based on the 

following primary criteria: 

+ Whether the responding provider(s) 

reported the child as UTD on certain 

key vaccines 

+ Whether the provider-reported 

vaccination dates matched the 

vaccination history reported by the 

household from a shot card 

+ Whether the child was UTD on the 

key vaccines when vaccinations 

after the date of the household 

interview were counted 

+ Whether the responding provider(s) 

reported at least as many doses of 

the key vaccines as the household 

respondent 

The rules were developed in 1995, 

when epidemiologic interest focused on 

the 4:3:1 vaccination series (4 or more 

doses of DTP, 3 or more doses of 

poliovirus vaccine, and 1 or more doses 

of any MCV). Thus, through 1998 the 

key vaccines were DTP, polio, and 

MCV. Since 1999 the key vaccines have 

been DTP, polio, MCV, Hib, and Hep B, 

which make up the 4:3:1:3:3 series (4 or 

more doses of DTP, 3 or more doses of 

poliovirus vaccine, 1 or more doses of 

any MCV, 3 or more doses of Hib, and 

3 or more doses of Hep B). 

By 2002 the scope of the NIS had 

expanded to include the VRC and PCV 

vaccines, but the rules for adequate 

provider data continued to use the 

4:3:1:3:3 series because the household 

questionnaire did not include those two 

vaccines in each quarter. As a result, in 

the years when the NIS collected 

histories on VRC and PCV, a child with 

adequate provider data may have a 

vaccination history that is incompletely 

ascertained for these vaccines. 

Among the 31,693 children for 

whom completed RDD interviews 

were obtained in 2002, 21,410 children 

were determined to have adequate 

provider data. Among these, 15,506 

(72.4 percent) were reported by the 

household respondent as having only 1 

vaccination provider. Among the 

remaining 5,904 sampled children who 

had 2 or more vaccination providers, 

3,127 (53.2 percent) did not have 

histories reported from all providers. 

When a child has two or more 

vaccination providers, the vaccination 

history may be scattered in such a way 

that no single provider has the entire 

history. A child’s vaccination history 

may be incompletely ascertained for one 

or more vaccines when not all providers 

contribute data and the reported 

information does not show that the child 

is UTD. Authoritative literature suggests 

that children with an incompletely 

ascertained vaccination status may be 

found to be UTD when their entire 

vaccination history from all providers is 

assembled and examined (16,17). 

Figure 2 shows the trend in the 

percentage of children with two or more 

providers from 1995 to 2002. This 

percentage stayed reasonably steady, 

ranging between 27 and 33 percentage 

points. Figure 2 also shows the trend in 

the percentage of children with two or 

more providers who have fewer than all 

providers reporting. This percentage 

ranged between 45 and 54 percentage 

points. 

Table 3 summarizes an analysis of 

factors associated with having two or 

more vaccination providers among 

children who had adequate provider data 

in the 2002 NIS. These results suggest 

that, compared with children with only 

one vaccination provider, children with 

two or more providers were significantly 

more likely to be Hispanic or 

non-Hispanic American Indian than 

non-Hispanic white; to have a mother 

who was not married than married, had 

fewer than 12 years of education rather 

than a college degree, preferred to speak 

Spanish rather than English during the 

interview, or who used a shot card; or, 
Series 2, No. 138 [ Page 7 

to live in a household that had an 

annual income of less than $75,000, had 

moved from another State since the 

child’s birth, or did not live in a 

metropolitan statistical area (MSA). 

Table 4 explores factors associated 

with incomplete ascertainment (response 

from fewer than all providers) among 

children with adequate provider data 

who had two or more providers. These 

results suggest that children who did not 

have response from all providers were 

significantly more likely to be Hispanic 

or foreign born; or to have a mother 

who was never married, had less than a 

high school education, preferred to 

speak Spanish, or was 20 years old or 

over; or lived in a household that had an 

annual income that was below poverty, 

or lived in the central city of an MSA. 

After adjusting for these factors among 

sampled children with two or more 

providers, incomplete ascertainment 

remained a significant predictor of 

4:3:1:3:3 vaccination coverage (p<0.05). 

Because of the potential for 

incomplete ascertainment of some 

children’s vaccination histories, users of 

NIS data who wish to compare 

vaccination coverage rates between subpopulations are cautioned to evaluate 

whether these differences are statistically 

significant after adjusting for differing 

rates of incomplete ascertainment between 

the subpopulations. ‘‘Evaluation of the 

Effect of Incomplete Ascertainment of 

Provider-reported Vaccination Histories 

on Estimates of Vaccination Coverage’’ 

provides a more thorough evaluation of 

this effect. 

Coverage of the Target 

Population, 2002 

NIS coverage of its target 

population, children 19–35 months of 

age, varies among the 78 IAP areas. To 

give a quantitative picture of that 

variation in 2002, table 5 presents 

measures of the ability of the NIS to 

access the target population and to elicit 

all of the desired data. The following 

paragraphs describe and discuss each of 

the numerical columns in table 5 (where 

the IAP areas are arranged in order of 

increasing value in column 9). 

Column 1: Percentage of children 

19–35 months in telephone households— 

For the United States as a whole in 

2000, a high percentage (92.8 percent) 

of age-eligible children reside in 

telephone households and, thus, are 

accessible to the RDD survey. 

California–Santa Clara County, at 

96.5 percent, had the highest percentage 

among IAP areas; however, 12 IAP 

areas were below 90 percent (the 

lowest were 86.7 percent in Arkansas, 

86.3 percent in Michigan–City of 

Detroit, and 85.3 percent in 

Mississippi). 

Column 2: Household eligibility 

rate (HER)—‘‘Section S’’ of the NIS 

RDD interview (‘‘The 2002 RDD 

Survey’’ and table A) yields information 

to determine whether a household 

contains any children 19–35 months of 

age. The HER is the percentage of 

telephone households that have children 

19–35 months of age. The HER for IAP 

areas ranged from 2.3 percent (District 

of Columbia) to 5.9 percent (Utah), with 

a median of 3.4 percent. 

Column 3: Eligibility benchmark 

(EB)—From sources external to the NIS 

it is possible to estimate the percentage 

of telephone households that have an 

age-eligible child, as a benchmark for 

the observed household eligibility rate. 

The public-use microdata samples from 

Census 2000 yielded a value of this 

eligibility benchmark for each IAP area 

Figure 2. Percentage of sampled children with two or more providers and with some 

providers not reporting among children with two or more providers: National Immunization 

Survey, 1995–2002 

and for the United States in 2000. For 

2002 the national eligibility benchmark 

from 2000 was updated by a scaling 

factor that reflected changes in the 

number of children 19–35 months of 

age (from unpublished NCHS natality 

data) and in the number of households 

(from U.S. Census Bureau projections). 

That scaling factor was then applied to 

the eligibility benchmark for each IAP 

area. The EB values for 2002 were 

consistently higher than the HER. The 

EB ranged from 3.4 percent (District of 

Columbia) to 8.1 percent (Utah), with a 

median of 4.7 percent. 

Column 4: Ratio of HER to 

EB—The ratio of HER to EB ranged 

from 0.55 (Shelby County, TN) to 0.85 

(South Dakota), with a median of 0.72. 

One plausible explanation for this 

relation, which the NIS has observed 

each year, is that a substantial number 

of households conceal age-eligible 

children. 

Column 5: Access rate—The access 

rate was the percentage of age-eligible 

children who live in a household with a 

residential telephone and are 

acknowledged in ‘‘Section S’’ of the 

NIS RDD interview. This rate is the 

product of columns 1 and 4. The access 

rate ranged from 50.3 percent (Shelby 

County, TN) to 79.1 percent (South 

Dakota), with a median rate of 

62.2 percent. 
Page 8 [ Series 2, No. 138 

Column 6: Interview completion 

rate—The interview completion rate 

was generally high among households 

that reported an age-eligible child. The 

interview completion rate ranged from 

85.1 percent (MD–City of Baltimore) to 

94.8 percent (Alaska), with a median 

rate of 90.6 percent. 

Column 7: Access rate × completion 

rate—This product approximates the 

percentage of children with a completed 

NIS RDD interview, among age-eligible 

children in the entire U.S. population. 

This rate ranged from 44.6 percent 

(Shelby County, TN) to 73.3 percent 

(Wyoming), with a median rate of 

59.7 percent. 

Column 8: Percentage of children 

with adequate provider data—For 

estimation of vaccination coverage the 

key ingredient is children who have 

adequate provider data. For the IAP 

areas in 2002 the percentage of children 

with adequate provider data (among 

children with a completed household 

interview) ranged from 50.6 percent 

(TX–City of Houston) to 79.8 percent 

(Vermont), with a median of 

68.2 percent. Only 8 IAP areas were 

below 60 percent, with TX–City of 

Houston (50.6 percent), NY–New York 

City (51.2 percent), and LA–Orleans 

Parish (54.2 percent) noticeably lower. 

Column 9: Access rate × completion 

rate × adequate provider data 

rate—This product summarizes the 

percentage of children with adequate 

provider data among age-eligible 

children who live in a household with a 

residential telephone, are acknowledged 

in ‘‘Section S’’ of the NIS RDD 

interview, and have a completed NIS 

RDD interview. This rate ranged from 

27.8 percent (LA–Orleans Parish) to 

56.6 percent (Vermont), with a median 

of 40.2 percent. 

Column 10: Percentage of children 

with complete provider response— 

‘‘Trends in Response Rates and Key 

Monitoring Statistics, 1994–2002’’ 

mentioned the challenge of incomplete 

ascertainment. Table 5 shows the 

percentage of children with complete 

provider response (i.e., all providers 

named by the household respondent 

supplied immunization information) 

among those with adequate provider 

data. This rate ranged from 70.5 percent 

(TX–City of Houston) to 92.4 percent 

(OH–Franklin County), with a median 

of 86.1 percent. 

Column 11: Access rate × 

completion rate × adequate provider 

data rate × complete provider 

rate—This product summarizes the 

percentage of children with complete 

provider response among age-eligible 

children who live in a household with a 

residential telephone, are acknowledged 

in ‘‘Section S’’ of the NIS RDD 

interview, have a completed NIS RDD 

interview, and have adequate provider 

data. This rate ranged from 21.5 percent 

(TX–City of Houston) to 50.6 percent 

(Vermont), with a median of 

34.2 percent. 

The product of the interview 

completion rate and the percentage of 

children with adequate provider data 

summarizes how representative the 

sample is among NIS age-eligible 

children living in households with a 

residential telephone and acknowledged 

by the NIS RDD respondent as living in 

the household. This rate ranges from 

46.7 percent (TX–City of Houston) to 

73.9 percent (Vermont), with a median 

of 61.5 percent. 

In each of these rate calculations 

the factors contributing toward 

diminishing the rates are the ratio of 

HER to EB (column 4: 0.70 percent 

nationally) and the percentage of 

children with adequate provider data 

(column 8: 67.3 percent nationally). The 

factors contributing least toward 

diminishing the rates are the percentage 

of children 19–35 months old living in 

households with telephones (column 1: 

92.8 percent nationally) and the 

percentage of children with complete 

provider response (column 10: 

84.7 percent nationally). 

Characteristics of Children 

in the NIS Sample, 2002 

As shown in table 2 (row 12), in the 

2002 NIS 31,693 children had 

completed RDD interviews, and 21,410 

children (67.6 percent) had adequate 

provider data (defined in ‘‘The 2002 

RDD Sample’’ and including 93 children 

who had received no vaccination doses). 

(See ‘‘Adjustment for Partial 

Nonresponse—Accounting for Children 

with No Vaccinations.’’) Table 6 shows 

the unweighted sample sizes and 

weighted percentage distributions of 

these two groups of children by a 

variety of child, maternal, and 

household characteristics. For each 

characteristic the percentage distribution 

of the subset of children with adequate 

provider data is closely similar to that 

for the children with a completed RDD 

interview. Thus, with the weights 

assigned by the 2002 NIS estimation 

methodology (see ‘‘Adjustment for 

Partial Nonresponse—Accounting for 

Children with No Vaccinations’’), the 

children with adequate provider data 

effectively represent the full RDD 

sample (weighted with the RDD-phase 

sampling weights). (See ‘‘The 

RDD-phase Sampling Weight’’ and 

‘‘Nontelephone Adjustments to the RDD 

Weights.’’) 

Estimation 

Methodology 

I

n preparation for calculating the 

estimates of vaccination coverage, 

the NIS assigns sampling 

weights to children who have a 

completed household interview, adjusts 

those weights (for reasons that include 

multiple residential telephone numbers, 

unit nonresponse, and noncoverage of 

nontelephone households), and 

incorporates data from providers (for 

children who have adequate provider 

data). Research led to major changes in 

the estimation methodology in 1998 and 

2002 as well as a variety of smaller 

improvements. This section describes 

these developments, with emphasis on 

the methodology as it stood in 2002. 

1994–97 Estimation 

Methodology 

For each year from 1994 to 1997 

the NIS used a variant of the two-phase 

sampling estimator to obtain estimates 

of vaccination coverage for each of the 

78 IAP areas. This method required 

survey weights for children whose 

parent or guardian completed the RDD 
Series 2, No. 138 [ Page 9 

interview. This report refers to this 

sampling weight as the ‘‘RDD-phase 

sampling weight’’ or, more compactly, 

the ‘‘RDD weight.’’ This section 

describes the adjustments that define the 

RDD weight and the two-phase 

sampling estimator. 

The RDD-phase Sampling 

Weight 

Between 1994 and 2001 the process 

of obtaining the RDD-phase sampling 

weight involved seven steps. The 

following paragraphs describe each of 

these steps and its purpose. 

Step 1: Base sampling weight— 

Each child sampled by the NIS receives 

a base sampling weight that is equal to 

the reciprocal of the probability of 

selecting the household’s telephone 

number into the sample. Specifically, 

this weight is the ratio of two totals for 

that IAP area: the number of telephone 

numbers in the 1+ working banks and 

the number of telephone numbers drawn 

from those banks and released for use. 

Step 2: Base sampling weight 

trimming adjustment—Some children 

actually reside in an IAP area adjacent 

to the one for which their household’s 

telephone number was sampled. Because 

a large range in the base weights can 

substantially increase the variance of 

estimates, the base weight for such a 

child is trimmed to no more than three 

times the base weight for the IAP area 

in which the child resides. 

Step 3: Multiple residential 

telephones adjustment—A household 

with two or more residential telephone 

numbers has a proportionally higher 

probability of being selected into the 

RDD sample. To preserve the 

relationship between the base sampling 

weight and this probability, an 

adjustment divides the trimmed base 

sampling weight by the number of 

nonbusiness voice-use telephone 

numbers reported in the household. 

Step 4: Multiple residential 

telephone weight trimming adjustment— 

Division of a household’s trimmed base 

sampling weight by the number of 

nonbusiness voice-use telephone 

numbers (Step 3) can introduce 

considerable variation in the adjusted 

weights. To reduce variation, the 

reported number of these telephones is 

trimmed to no more than three. This 

adjustment incurs a small amount of 

bias. 

Step 5: Household unit nonresponse 

adjustment—Unit nonresponse occurs 

because some of the sample telephone 

numbers with age-eligible children are 

never determined to be residential 

telephone numbers despite multiple call 

attempts; or they are determined to be a 

residence but cannot be determined to 

have age-eligible children; or they are 

residences with age-eligible children for 

whom the RDD interview is not 

completed. To account for these three 

types of unit nonresponse, the sampling 

weights of children with a completed 

RDD interview are adjusted for the 

estimated number of age-eligible 

children in households that are never 

determined to be residential telephone 

numbers, the estimated number of 

age-eligible children in households that 

fail to complete the screening interview, 

and the number of children in identified 

age-eligible households for whom the 

RDD interview is not completed. Each 

adjustment is tailored to account for 

variation of these factors within IAP 

areas related to the socioeconomic 

characteristics of children in the sample 

and the corresponding composition of 

the population in sampled telephone 

exchanges. That is, unit nonresponse 

adjustments are made within cells 

formed using telephone-exchange 

characteristics. These cells are defined 

by cross-classifying the residential 

directory-listed status of the sample 

telephone number by at least one of four 

telephone-exchange-level variables: 

MSA status, percentage of households 

that are owner-occupied, percentage of 

the adult population that are college 

graduates, and percentage of the 

population that is non-Hispanic white. 

Step 6: Nontelephone coverage 

adjustment—RDD yields a sample of 

children in households that have 

telephones, but the NIS aims to measure 

vaccination rates for all children 19–35 

months of age. Data from the NHIS 

indicated that vaccination levels are 

generally lower among nontelephone 

children than among telephone children. 

In some IAP areas a substantial 

proportion of age-eligible children reside 

in nontelephone households. To 

compensate for such potential 

noncoverage bias, the NIS employs a 

weight-adjustment procedure described in 

‘‘Nontelephone Adjustments to the RDD 

Weights’’ and by Battaglia et al. (18). 

Step 7: Poststratification 

adjustment—Poststratification separates 

the actual sample into cells defined by 

characteristics that are related to 

noncoverage and to vaccination status: 

education of the mother, race/ethnicity 

of the mother, and age group of the 

child (discussed further in 

‘‘Nontelephone Adjustments to the RDD 

Weights’’). Then, the weighted 

distribution of completed interviews 

over the cells is brought into agreement 

with a corresponding set of population 

totals of these birth cohorts derived 

from NCHS natality data. This 

adjustment reduces bias incurred by 

obtaining samples whose weighted totals 

do not agree with known population 

totals of variables that are believed to be 

associated with being vaccinated. In 

RDD surveys these differences often 

arise from differential nonresponse. 

The Two-phase Sampling 

Estimator 

In surveys like the NIS that have 

two phases of data collection, two-phase 

sampling estimators (described by 

Cochran) often have been used to adjust 

for nonresponse at the second 

phase (19). This section describes how 

the NIS implemented this methodology 

to obtain vaccination coverage rates 

between 1994 and 1997. 

A child is said to be ‘‘4:3:1:3 

UTD’’ provided he or she has received 4 

or more doses of DTP or DTaP, 3 or 

more doses of polio, 1 or more doses of 

MCV, and 3 or more doses of Hib. 

Within an IAP area, each child with a 

completed interview was categorized 

into one of five strata according to 

whether the household respondent 

reported that the child was 4:3:1:3 UTD 

and whether a shot card was used 

during the household interview. These 

strata are described below. 

Stratum 1: Household respondent 

had a shot card during the RDD 

interview and reported the eligible child 

as being 4:3:1:3 UTD. 
Page 10 [ Series 2, No. 138 

Stratum 2: Household respondent 

had a shot card during the RDD 

interview and reported the eligible child 

as not being 4:3:1:3 UTD. 

Stratum 3: Household respondent 

did not have a shot card during the 

RDD interview and reported from recall 

the eligible child as being 4:3:1:3 UTD. 

Stratum 4: Household respondent 

did not have a shot card during the 

RDD interview and reported from recall 

the eligible child as not being 4:3:1:3 

UTD. 

Stratum 5: Information was missing 

on 4:3:1:3 UTD status and/or shot card 

use. 

Table B shows the percentage 

distribution of children over these five 

strata in 1997, along with the percentage 

whose providers reported they were 

4:3:1:3 UTD (among children who had 

adequate provider data). The provider 

data indicate substantial response biases 

in the household reports, in both 

directions. In Stratum 1 and Stratum 3, 

though the household respondent 

reported the child UTD, only 

87.6 percent and 77.2 percent, 

respectively, were reported as UTD by 

their providers. Conversely, in Stratum 2 

and Stratum 4, though the household 

reported the child not UTD (NUTD), 

68.6 percent and 70.8 percent, 

respectively, were reported as actually 

UTD by their providers. 

Children in Stratum 1 were said to 

belong to the ‘‘top row.’’ These children 

were 4:3:1:3 UTD according to their 

shot card. Of the NIS children with 

completed household interviews in 

1997, 28.4 percent belonged to the top 

row. As described below, the two-phase 

estimator in the NIS handled the top 

row in a special way. 

pˆ

Using the RDD weights, let pˆ1,ij 

denote in IAP area i the estimated 

weighted proportion of children who 

belong to Stratum j, j = 1,...,5. Also, let 

2,ij denote the estimated weighted 

proportion of children in IAP area i 

belonging to Stratum j who are 

determined to be 4:3:1:3 UTD from data 

obtained from the providers in the 

second phase of sampling. Then, the 

two-phase sampling estimator for the 

4:3:1:3 vaccination coverage rate in IAP 

area i is 

Table B. Strata based on household’s report of child’s 4:3:1:3 up-to-date status and 

household’s use of shot card, percentage distribution of children by stratum, and 

percentage of children in each stratum who are 4:3:1:3 up to date in providers’ reports: 

National Immunization Survey, 1997 

Percent UTD 

Percent from providers’ 

distribution reports 

Stratum (unweighted) (weighted)1 

Shot card, 4:3:1:3 up-to-date ................. 28.4 87.6 

Shot card, not 4:3:1:3 up-to-date ............... 20.7 68.6 

No shot card, 4:3:1:3 up-to-date ............... 16.7 77.2 

No shot card, not 4:3:1:3 up-to-date ............. 15.4 70.8 

Shot card or 4:3:1:3 status missing ............. 18.8 72.9 

1UTD is up-to-date. 

NOTE: 4:3:1:3 refers to 4 or more doses of diphtheria and tetanus toxoids and pertussis vaccine (DTP), 3 or more doses of polio 

vaccine (polio), 1 or more doses of measles-containing vaccine (MCV), and 3 or more doses of Haemophilus influenzae type b 

vaccine (Hib). 

5 

ˆπi = ∑ pˆ1,ij pˆ2,ij 

j=1 [1] 

The NIS implementation involved a 

special modification of this two-phase 

sampling estimator. Specifically, 

weighted data from the entire national 

sample of children belonging to Stratum 

1 (i.e., the top row) with adequate 

provider data were used to estimate pˆ2,i1 

for every IAP area. Parallel to the 

definition for the 4:3:1:3 series given 

previously, each vaccine or series had its 

own pˆ2,ij. In addition, for estimation of 

Hep B coverage, the definitions of the 

five strata were based on the 

household’s report of the child’s UTD 

status on Hep B rather than on 4:3:1:3. 

The resulting provider-adjusted top-row 

estimator was used in the NIS before 

1998. It reduced the impact of IAP areas 

where a substantial proportion of 

top-row children were not 4:3:1:3 UTD 

in their provider data. This situation was 

thought to be caused primarily by 

incomplete provider records. A further 

description of the NIS estimation 

methodology used before 1998 can be 

found in Zell et al. (8). 

One disadvantage of the provideradjusted estimator is that it tends to 

produce a slightly biased estimate of 

IAP area vaccination coverage rates. 

Using national data to estimate pˆ2,i1 

tends to bias coverage estimates for IAP 

areas toward the national figure. 

An additional disadvantage is that 

few methods are tailored for statistical 

analyses of data from two-phase 

sampling designs when the analysis calls 

for more-complicated models. For 

example, epidemiologic analyses of 

complex survey data routinely require 

logistic regression. However, no 

standard statistical methods for logistic 

regression that account for a two-phase 

sampling design have been developed 

and made accessible to analysts through 

commonly available commercial 

software. So, although weighted 

estimates reflecting both phases of 

sampling can be produced, limitations 

exist for more-complex epidemiologic 

analysis and for release of data on 

public-use files. 

Because of these disadvantages, a 

different statistical estimation 

methodology was implemented in 

1998 (6). The next section describes this 

methodology. 

1998–2001 Estimation 

Methodology 

As discussed previously, the NIS 

has two phases of data collection. The 

first phase collects demographic and 

other descriptive data from households 

using list-assisted RDD sampling. The 

RDD weights then account for the 

probability of being selected from the 

sampling frame, nonsampling error 

resulting from unit nonresponse and/or 

failure to complete the first phase, and 

other adjustments such as poststratification. At the end of the first 

phase of data collection, respondents are 

asked for consent to allow survey staff 

to contact their children’s medical 

providers. With consent, the second 
Series 2, No. 138 [ Page 11 

phase asks the medical providers to 

report on aspects of the children’s 

vaccination histories. 

In the remainder of this report the 

term ‘‘partial response’’ refers to the 

response pattern in which data are 

obtained from respondents in the first 

phase of the survey but provider data 

are not obtained in the second phase. 

The term ‘‘complete response’’ refers to 

response patterns in which data are 

obtained in both phases. 

When complete responders and 

partial responders have very different 

characteristics and the proportion of 

partial responders is at least moderately 

large, survey estimates may be severely 

biased. This partial-nonresponse bias can 

arise when the estimates are based only 

on data from complete responders, without 

adjusting for differences between complete 

and partial responders. 

Brick and Kalton indicate that the 

most common method of adjusting for 

partial-nonresponse bias in health 

surveys is by using weighting classes, 

also called adjustment cells (20). This 

method assigns each complete responder 

and each partial responder to an 

adjustment cell within which sampled 

persons are comparable. Within the cell 

the adjustment redistributes the firstphase sample weights of the partial 

responders equally among the complete 

responders so that (with their adjusted 

first-phase sample weights) the complete 

responders represent the population in 

the cell. 

The purpose of the weighting-class 

method is to compensate for potential 

bias in estimation that would result if 

the factors associated with partial 

response were ignored and estimates 

were prepared without accounting for 

differences between complete and partial 

responders. Weighting classes are 

defined by factors believed to be 

associated with these differences. Within 

each adjustment cell it is assumed that 

partial responders’ provider data are 

missing at random (21,22). This 

assumption implies that, within a cell, 

complete and partial responders are 

comparable, and any estimate that uses 

data only from the complete responders 

(along with their adjusted first-phase 

sample weights) should have little bias 

attributable to differences between 

complete and partial responders. 

Suitably aggregating the estimates from 

all weighting classes yields a 

population-level estimate that has 

reduced bias attributable to such 

differences. 

The NIS estimation methodology 

used between 1998 and 2001 was based 

on weighting classes; it yielded survey 

weights for complete responders that 

were used, along with their vaccination 

history data, to obtain estimates of 

vaccination coverage rates. This report 

refers to these survey weights as 

‘‘partial-nonresponse-adjusted sampling 

weights.’’ The specific steps in the 

process consisted of adjusting the RDD 

weights of complete responders using 

weighting classes and then raking the 

adjusted weights so that their sums for 

specific demographic cells corresponded 

to known or estimated totals. The next 

two subsections describe these two 

steps. 

Adjustment of Complete 

Responders’ RDD Weights 

To adjust the RDD weights so that 

coverage estimates could be based on 

data only from complete responders, 

weighting classes were formed using 

response propensities obtained from a 

logistic regression model whose 

response variable indicated whether a 

child was a complete responder. Within 

each IAP area, sampled children can be 

grouped into weighting classes 

according to the similarity of their 

response propensities to be a complete 

responder. Children with similar 

response propensities have similar 

probabilities of having adequate 

provider data. A group of children who 

have similar response propensities will 

also be similar with respect to 

characteristics that are strongly 

associated with the probability of having 

adequate provider data. In this important 

respect, children within each weighting 

class are comparable; thus, all of the 

sampled children in the class may be 

represented by the complete responders. 

In particular, by dividing the RDD 

weights of children with adequate 

provider data by the weighted response 

rate for the class, these children’s 

weights are adjusted to represent all of 

the children belonging to the class. 

Thus, the bias in estimated vaccination 

coverage rates attributable to differences 

between sampled children who have and 

do not have provider-reported 

immunization histories is reduced. 

Within each weighting class, children 

without adequate provider data are 

represented by children who have 

similar response propensities and other 

associated characteristics. 

To obtain the response propensities, 

a national model was developed using 

logistic regression. Within each IAP area 

the RDD weights were first rescaled so 

that their sum equaled the IAP-areaspecific sample size. Inclusion of these 

rescaled weights as prior weights in the 

logistic regression ensured that the 

regression coefficients would have the 

property that, as the sample size 

increases to the finite population size, 

the estimated coefficients converge to 

the true finite-population values, provided 

the logistic model and its linear predictors 

correctly depict why provider vaccination 

histories are missing. 

The candidates for predictors in the 

response propensity model were 

variables that have been found to be 

associated with immunization status in 

other research conducted by CDC (23). 

Table C lists variables used as 

candidates for the model in 2002. 

Forward stepwise logistic regression was 

used to select predictors among these 

candidates. SPlus 2000 was used for all 

calculations (24). 

At each step of the stepwise 

selection process, the logistic regression 

model examined the main effects of 

each predictor. Also, at each step after 

adding regressors to the model, the 

model-selection method re-examined 

each regressor in the model to determine 

whether any predictor that entered at a 

previous step could be dropped. 

Akaike’s Information Criterion (AIC) 

guided the choice of the optimal set of 

candidate regressors at each step (25). 

AIC provides a measure of goodness of 

fit of a model, corrected for the number 

of parameters in the model. Within this 

framework a model with minimum AIC 

provides the best fit to the data. Also, 

deviance provides a related measure of 

goodness of fit measured on the scale of 

–2 times log likelihood. The asymptotic 
Page 12 [ Series 2, No. 138 

Table C. Variables used in the model selection for the response propensity model: National distribution of the difference of 

Immunization Survey, 2002 deviances for two nested models is a 

Variable name Description and levels chi-squared distribution with degrees of 

agegrp 

1 

2 

3 

c5 

1 

2 

3 

4 

childnm 

1 

2 

3 

educ1 

1 

2 

3 

4 

frstbrn 

1 

2 

incpov1 

1 

2 

3 

4 

m.agegrp 

1 

2 

3 

marital 

1 

2 

3 

mobil 

1 

2 

msa 

1 

2 

3 

racekid 

1 

2 

3 

4 

5 

sex 

1 

2 

shot card 

1 

2 

Child’s age: 

19–24 months1 

25–29 months 

30–35 months 

Relationship of the household respondent to the child: 

Mother (step, foster, adoptive) or female guardian1 

Father (step, foster, adoptive) or male guardian 

Other 

Unknown 

Number of children under 18 years of age living in the household: 

1 child1 

2–3 children 

4 or more children 

Educational status of the mother: 

Less than 12 years1 

12 years 

More than 12 years, not college graduate 

College graduate 

Firstborn status of child: 

Not firstborn1 

Firstborn 

Annual income and poverty status: 

Above poverty, $75,000 or more1 

Above poverty, less than $75,000 

Below poverty 

Unknown 

Maternal age group: 

19 years or under1 

20–29 years 

30 years or over 

Marital status of the mother (or deceased) 

Widowed/divorced/separated/deceased1 

Never married 

Married 

Mobility status 

Moved from different State1 

Did not move from a different State 

Household MSA status2

: 

MSA, central city1 

MSA, not in central city 

Not MSA 

Race/ethnicity of the child: 

Hispanic1 

Non-Hispanic white and other races 

Non-Hispanic black 

Non-Hispanic American Indian 

Non-Hispanic Asian 

Sex of the child: 

Male1 

Female 

Household reported immunization status using a shot card: 

Shot card used during RDD interview1,3 

Shot card not used during RDD interview 

freedom equal to the difference in the 

number of parameters indexing the two 

models. McCullagh and Nelder discuss 

the use of the deviance as a way of 

evaluating the statistical significance of 

predictors in a model (26). For the 2002 

NIS the eight predictor variables (in 

order of entry, after the constant term) 

in the response-propensity model for 

whether a child has adequate provider 

data are poverty status; relationship of 

the household respondent to the child; 

household-reported immunization status 

using a shot card; household within 

central city of MSA, suburban, or 

nonmetro area; educational status of the 

mother; mobility status; race/ethnicity of 

the child; and number of children in the 

household. 

The final model obtained from the 

variable-selection process yielded a 

predicted response propensity for each 

sampled child. Within each IAP area 

five weighting classes were formed, 

with boundaries defined by quintiles of 

the distribution of the response 

propensities. Each sampled child 

belonged to one of these weighting 

classes. Within each weighting class the 

complete responders’ RDD weights were 

divided by the weighted response rate in 

the class. In this way, the RDD weight 

for all children in a class was 

proportionally redistributed among the 

complete responders in that class, 

producing adjusted RDD weights. 

Raking the Adjusted Sampling 

Weights of Complete 

Responders 

Within an IAP area the sums of 

adjusted sampling weights of complete 

responders for the various levels of 

important demographic variables (such 

as race/ethnicity) may not be equal to 

1This is the reference level for this variable. 

2MSA is metropolitan statistical area. 

3RDD is random-digit-dialed. 

corresponding population totals. To 

reduce bias attributable to these 

differences, iterative ratio adjustment 

was used to rake the adjusted weights to 

match poststratification totals (27). 

Table D lists the variables used for 

raking in 2002. Control totals for these 

variables were estimated using the 
c 

1 

Series 2, No. 138 [ Page 13 

Table D. Variables used for raking the response-propensity-adjusted sampling weights of δ' hij = 1 when the j-th sampled subject children with provider data: National Immunization Survey, 2002 in the i-th sampled PSU of 

Variable name Variable description stratum h belongs to the domain 

of interest, and δ' hij=0, otherwise. educ1 Educational status of the mother 

racekid1 Race/ethnicity of the child Letting 

agegrp Age group of the child 

∑ ∑ i=1 j

Nh Mhi 

=1 

1This variable was also used to provide a poststratification adjustment to the random-digit-dialed weights. Mother’s race/ethnicity and 

was used for poststratification. 

Nh Mhi 

sex Sex of the child 

Y δ Yhij frstbrn Firstborn status of the child = h hij adj.cell Adjustment cell to which each child belongs within each immunization action plan area 

∑ 

j=1 

sample. Vaccination Coverage the true but unknown vaccination rate 

For a particular stratum, let n for the domain is 

denote the number of complete Estimates of vaccination coverage 

responders, and let W1

(0),...,Wn (0) denote in the NIS are weighted proportions of L 

∑ 

i=1

Th = δhij

weighted totals from the first-phase The Ratio Estimator of 

∑ 

h=1

Yh 

L 

their partial-nonresponse-adjusted children who are UTD, often in some 

sampling weights (before any raking). domain of interest. Formally, those 

Also, let Lv denote the number of levels proportions are ratio estimators, either θ = 

for the v-th demographic raking within a stratum (i.e., an IAP area) or 

variable, and let Xvlc=1 if the c-th combining the data from the strata. In 

complete responder belongs to the l-th this section, let L denote the number of 

level of the v-th demographic raking strata, and let Let 

∑ 

h=1

Th 

variable and 0 otherwise, v=1,...,V, 

l=1,2,...,Lv . Finally, let Tvl denote the ∑ 

i=1

nh 

Y|h ∑ 

j

mhi 

δ' hij

=1 

Nh = the number of primary sampling = W Y' units (PSUs, or households in the 

NIS) in stratum h; 

hij hij 

population total in the stratum for the 

v-th raking variable at its l-th level. 

Each iteration of the raking process nh = and the number of PSUs sampled in 

stratum h, h=1,...,L;

∑ 

j

∑ 

i=1 

nh mhi 

=1 

of stratum h belonging to the Then the combined ratio estimator of 

takes one variable in turn (v=1,...,V) and δ' hij T|h Whij = makes a multiplicative adjustment for 

each level of that variable (l=1,...,Lv). 

Mhi = the number of subjects in PSU i 

At the i-th iteration, (i=1,2,...), the 

partial-nonresponse-adjusted sampling target population; the vaccination rate for the domain of 

{W

weights from the (i–1)-th iteration, mhi = the number of subjects in PSU i interest is 

(i–1)}, for complete responders of stratum h who were sampled 

belonging to the l-th level of the current in the survey; L 

∑ 

h=1

Y|h 

L 

variable (v* ) are raked to yield Whij = the overall sampling weight for ^ subject j sampled in PSU i of θ = Tv

*

l 

W(i) = W(i–1) stratum h, accounting for all ∑ 

h=1

T|h 

c c n sampling and nonsampling ∑
W [2] (i–1)

c X adjustments; * v lc c=1 

Yhij = 0 when subject j in PSU i of l=1,2,...,L The Taylor-series Estimate of v

*. If v* 

=V and n stratum h is NUTD on a specific 

|

Tvl – Σ Wc 

(i) Xvlc| <1 for all vaccination, and Yhij = 1 when the Variance 

l=1,2,...,Lv and all v=1,...,V, child is UTD; Letting iteration stops. Otherwise, at the next 

c=1 

δhij = 1 when subject j in PSU i of iteration the process rakes each level of L 

∑ * stratum h belongs to the domain Zhij = ( ) – ^

θ the (v +1)-th variable (or the first [ ] –1 T| δ' h hijWhij (Y' ) of interest, and δhij=0, otherwise; hij variable, if v* 

=V). To maintain the effect h =1 

of the partial-nonresponse adjustment, Y' hij = 0 when the j-th sampled subject 

adjustment-cell membership is included in the i-th sampled PSU of denote the linearized value of the ratio among the raking variables. Deville et stratum h is NUTD on a specific estimator [2] and letting al. discuss more-general raking vaccination, and Y' hij=1 when the 

procedures (28). child is UTD; and mhi nh 

∑ 

j

Zhi 

=1 

Zhij and Zh = (nh)

–1 ∑ 

i=1

= Zhi 
Page 14 [ Series 2, No. 138 

the Taylor-series estimate of the 

variance of |θ is (neglecting higher-order 

terms) 

L nh nh 

V|T (θ

^)= ∑ nh–1 ∑ (Zhi – Zh)

2 

h=1 i=1 [3] 

2002 Estimation 

Methodology 

In 2002 a different approach to 

adjusting the RDD weights produced a 

more accurate accounting within each 

IAP area for households that do not 

have telephones. Also, the procedure for 

obtaining partial-nonresponse-adjusted 

sampling weights of children with 

adequate provider data was revised to 

account for children who have had no 

vaccinations. This section details the 

procedures used before 2002, describes 

the changes for 2002, and examines the 

effect of the two modifications. 

Nontelephone Adjustments to 

the RDD Weights 

Background 

The NIS relies on RDD to obtain a 

sample of children 19–35 months of age 

in each IAP area. A key disadvantage of 

the RDD sampling approach is that it 

gives children residing in nontelephone 

households a zero probability of 

selection. Although one can use an RDD 

sample to generalize to the population 

of age-eligible children in telephone 

households in a straightforward manner, 

the objective of the NIS is to generalize 

to the entire population of age-eligible 

children residing in households in each 

IAP area. 

The accuracy of estimates obtained 

from the NIS will be affected by the 

proportion of age-eligible children 

residing in nontelephone households and 

by the difference in vaccination rates 

between telephone and nontelephone 

children. Although an estimated 

90 percent of 2-year-old children in the 

United States resided in a household 

with a telephone in 1996–97, the 

percentage for IAP areas (table 7) 

ranged from 76 percent (Arkansas) to 

97 percent (Pennsylvania–Rest of State). 

Table 7 also shows the corresponding 

percentage in 2000 from lowest to 

highest, based on the 2000 census and 

information from the March 2000 

Current Population Survey (CPS). Many 

IAP areas had higher telephone coverage 

in 2000. The Federal Communications 

Commission (FCC) has also reported an 

increase in the percentage of U.S. 

households with telephone service: 

93.9 percent in March 1997, 

94.6 percent in March 2000, and 

95.5 percent in March 2002 (29). 

Although telephone coverage has 

increased over recent years, the number 

of telephone lines has decreased since 

2000. The FCC attributes this to the 

recession, elimination of second 

telephone lines when households move 

from dial-up Internet service to 

broadband or cable-modem service, and 

substitution of wireless service for 

wireline service. 

Data on vaccination coverage and 

household telephone status have been 

collected by the NHIS (in its 

Immunization Supplement) and by the 

National Immunization Provider Record 

Check Study (NHIS/NIPRCS), which 

collected provider-reported vaccination 

histories of children sampled in the 

Immunization Supplement (30). Those 

data indicated that vaccination coverage 

rates for 19–35-month-old children 

differ considerably between telephone 

and nontelephone households. The 

sizable percentages of nontelephone 

households in many IAP areas and the 

large differences in vaccination coverage 

between telephone and nontelephone 

children suggest that vaccination 

coverage estimates that use only 

telephone households could have 

considerable bias. Thus, NIS estimation 

methods attempt to adjust for 

differences between telephone and 

nontelephone children. 

Initial evidence on approaches to 

adjustment for noncoverage in the NIS 

came from an analysis of the 1992 

NHIS sample of children 19–35 months 

of age. An initial hypothesis in the NIS 

was that demographic and socioeconomic characteristics could account 

for the relationship between having a 

telephone in the household and being 

UTD on vaccinations. A positive finding 

would suggest that poststratifying the 

NIS sample of telephone children on 

those demographic and socioeconomic 

characteristics could reduce noncoverage 

bias. To test this hypothesis, logistic 

regression models related indicators of 

UTD vaccination coverage to a set of 

demographic and socioeconomic 

predictors, both individual-level and 

county-level variables. Adding an 

indicator for the presence of a telephone 

produced a statistically significant 

improvement in each model. This result 

indicated that, for the 1992 NHIS, the 

demographic and socioeconomic 

variables could not adequately account 

for the effect of telephone ownership on 

vaccination coverage. 

The process of developing 

alternative estimation techniques to 

adjust for noncoverage of children in 

nontelephone households began with a 

review of past research. In a 

comprehensive review of weighting 

procedures for RDD samples, Massey 

and Botman discuss adjustments to the 

base sampling weight to account for 

households without telephones (31). In a 

specific example, they multiply the base 

sampling weight by the ratio of the 

estimated total population to the 

estimated telephone population within a 

set of cells defined by geographic region 

and race. They also suggest 

poststratification as a way to reduce 

noncoverage bias. In their evaluation of 

an RDD survey on smoking behavior, a 

comparison with the NHIS sample 

seems to indicate that the weighting 

adjustments were partially successful in 

accounting for telephone coverage bias. 

A National Center for Education 

Statistics study examining schooling 

variables in the CPS found that 

poststratifying the sample of telephone 

individuals was not always successful in 

reducing noncoverage bias (32,33). The 

investigators found that multiplying the 

base sampling weight by the ratio of 

total population to telephone population 

for three categories of school-enrollment 

status within each poststratification cell 

before carrying out the usual poststratification adjustment sometimes led 

to a greater reduction in noncoverage 

bias than poststratification alone. The 

general conclusion from reviewing the 

literature was that a single estimation 

procedure may not always be the most 

successful in reducing noncoverage bias 

in an RDD sample. 
Further work on NIS estimation 

procedures (described below) focused on 

poststratification. Simple poststratification 

served as a starting point and as a basis 

for assessing the further reduction in 

noncoverage bias that could be achieved 

by modified poststratification, which 

used estimates from the NHIS/NIPRCS 

on the ratio of vaccination coverage 

rates for nontelephone children to the 

corresponding rates for telephone 

children. 

Simple Poststratification 

A widely-used estimation technique 

for an RDD sample poststratifies the 

nonresponse-adjusted base sampling 

weight. That is, the weighted 

distribution of the completed interviews 

is brought into agreement with the 

population control totals for a set of 

poststratification cells. This method is 

called ‘‘simple poststratification.’’ For 

example, a sample that is poststratified 

on the combination of three age 

categories and two gender categories 

would have six poststratification cells. 

The NIS can obtain population control 

totals from unpublished NCHS natality 

data files. The general idea is to select 

variables that are related to unit 

nonresponse and/or noncoverage and are 

associated with the key subject-matter 

variables. NCHS natality data include 

variables such as date of birth, race of 

mother, Hispanic origin of mother, and 

education of mother. These variables, as 

demonstrated in the analysis of the 1992 

NHIS, are related to noncoverage and 

vaccination status. 

One major drawback is that simple 

poststratification assumes that the 

percentage vaccinated within each 

poststratification cell is the same for 

both telephone and nontelephone 

children. Most of the estimates of 

vaccination coverage produced by the 

NIS can be characterized as UTD 

estimates. That is, a child is considered 

UTD if he or she has received at least a 

specified number of vaccinations. One 

of the primary estimates is the 

percentage of children who were UTD 

on DTP, polio, and MCV (i.e., 4 or 

more DTP, 3 or more polio, and 1 or 

more MCV). The analysis of the 1992 

NHIS indicated that the percentage of 

19–35-month-old children who were 

UTD on DTP, polio, and MCV was 

lower for nontelephone children than for 

telephone children within the categories 

of the potential poststratifiers. This 

result suggests that simple poststratification will be only partially 

successful in eliminating noncoverage 

bias. It does, however, provide a framework for modified poststratification. 

Simple poststratification in the NIS 

serves primarily to adjust for 

noncoverage of nontelephone 

households and secondarily to 

compensate for unit nonresponse. The 

population control totals must 

correspond to variables that are 

collected for respondents. The NIS 

questionnaire obtains State and county 

of residence, race of child, Hispanic 

origin of child, age of child in months, 

race of mother, Hispanic origin of 

mother, and education of mother. NCHS 

natality data are the only source for 

IAP-area-specific population control 

totals based on children’s age in months 

during a 4-quarter period (34). 

Specifically, the population control totals 

for a 4-quarter period are based on birth 

records for children born 19–35 months 

prior to the midpoint of that period. The 

natality data file contains all the above 

variables as well as month and year of 

birth, age of mother, education of father, 

and MSA identification codes as of June 

30, 1990. (Subsequently the MSA codes 

were updated, effective with 1996 data, 

to reflect the results of the 1990 census.) 

For a small percentage of birth records, 

Hispanic origin of mother and/or 

education of mother was missing. A 

hot-deck procedure, basing imputation 

cells on State and race, was used to fill 

in those missing data. 

Formation of Poststratification Cells 

The natality data files yield 

population control totals for each of the 

78 IAP areas. In developing this process 

the first step was to prepare a 

cross-tabulation for each IAP area, 

showing the distribution of live births 

for education of mother by race of 

mother by Hispanic origin of mother by 

MSA status of residence county. 

Tabulations that included age of child 

were also developed. 

These cross-tabulations were 

analyzed, and rules were developed for 

Series 2, No. 138 [ Page 15 

collapsing cells of the cross-tabulation 

into a set of poststratification cells for 

each IAP area. This analysis aimed to 

create a reasonable number of 

poststratification cells from a potentially 

large number of cross-classification 

cells. The poststratification for Q2 and 

Q3 of 1994 used three cells within each 

IAP area: mother’s education less than 

12 years; mother’s education 12 years or 

more and child 19–25 months old; and 

mother’s education 12 years or more 

and child 26–35 months old. 

For the combined data from Q2, 

Q3, and Q4 of 1994 (and for data from 

four consecutive quarters), the process 

introduced race/ethnicity as an 

additional poststratification variable and 

constructed poststratification cells 

separately for each IAP area. The 

hierarchical process for constructing the 

cells used race/ethnicity as the first 

variable (with three categories: Hispanic, 

non-Hispanic black, and non-Hispanic 

white or other), mother’s education as 

the second variable (two categories: 12 

years or less and more than 12 years), 

and age of child as the third variable 

(two categories: 19–25 months and 

26–35 months). To remain separate, a 

category had to contain enough children 

with completed interviews to satisfy the 

following minimum sample size 

requirements: 

+ 25 for a category of race/ethnicity 

+ 30 for a category of mother’s 

education 

+ 30 for a category of child’s age 

If either the Hispanic category or 

the non-Hispanic black category had 

fewer than 25 children with completed 

interviews, it was first combined with 

the other minority category to see 

whether the resulting sample size 

exceeded 25. After comparing the 

weighted age distribution of the NIS 

sample against that in the natality file, the 

minimum sample size for an age category 

was reduced to 25 in nine IAP areas. 

To illustrate the construction of 

poststratification cells, table 8 shows the 

initial data and the result for the 

Massachusetts–City of Boston IAP area. 

In the cross-classification of sample 

children by race/ethnicity, education of 

mother, and age of child, all three 

race/ethnicity categories exceed the 
Page 16 [ Series 2, No. 138 

minimum sample size requirement of 25 

children. 

Education of mother is then 

examined. For Hispanic children the 

more than 12 years category for 

education of mother contains fewer than 

30, but each of the other two 

race/ethnicity categories has more than 

30 children in both education-of-mother 

categories. Therefore, non-Hispanic 

black and non-Hispanic white or other 

children are split into the two 

education-of-mother cells, and no 

education split is made for Hispanic 

children. 

Age of child is examined next. 

Hispanic children cannot be split on age 

because the 19–25-month age category 

contains fewer than 30 children. 

Non-Hispanic black children whose 

mothers have 12 or less years of 

education cannot be split on age of 

child. The same holds for non-Hispanic 

black children whose mothers have 

more than 12 years of education. For 

non-Hispanic white or other children the 

lower-education cell has 23 children in 

the 19–25-month age category, and 

therefore no split on age is made. The 

higher-education cell has more than 30 

children in both age categories, 

however, and these children are split on 

age. As shown in the second panel of 

table 8, the process yields a total of six 

poststratification cells for the 

Massachusetts–City of Boston IAP area. 

After reviewing the results for 

Q2–Q4/1994, it was decided to use the 

same set of poststratification cells in 

each IAP area for each subsequent 

4-quarter period of the NIS. However, if 

one of those cells contained fewer than 

20 children, it was combined with an 

adjacent cell. 

The Natality Data 

The NCHS natality file provides a 

universe of live births in the United 

States. Using these data to form the 

required population control totals of 

19–35 months of age for the NIS 

requires adjustments for infant mortality, 

immigration into the United States, and 

emigration from State to State. To adjust 

for infant mortality in the native-born 

U.S. population, State-specific rates of 

infant mortality by race group (obtained 

from NCHS) are applied. 

Next, an adjustment to the 

mortality-corrected NCHS natality 

counts is made to account for children 

who immigrate into the United States 

before reaching the age of 19–35 

months. This immigration adjustment 

increases the population of children. The 

public-use microdata samples (PUMS) 

from the 1990 census were used to 

estimate the number of 2-year-olds in 

each State who were born outside the 

United States. 

Lastly, the mortality-andimmigration-adjusted NCHS natality 

counts used for NIS control totals are 

adjusted for emigration from State to 

State. The average annual interstate 

migration rate for children 1–4 years of 

age is 3.6 percent. To examine this issue 

in more detail, 1990 census data were 

used to estimate the percentage of 

2-year-old children who had been born 

outside their State of residence. A 

different State of birth would indicate 

migration over the 2-year period or that 

the child was born in a hospital outside 

the State of residence (e.g., the State of 

residence was Maryland, but the child 

was born in a hospital in the District of 

Columbia). In general, a nontrivial 

percentage of 2-year-old children were 

born in a different State than their State 

of residence. Thus, inter-IAP-area 

migration might reduce or inflate the 

population control totals for a given IAP 

area. The 1990 census data, however, 

permitted estimation of net migration 

only for States, not for individual IAP 

areas. Given the limitations of the data, 

a simple State-by-State adjustment for 

net migration was made. 

The ratio of the adjusted count to 

the original count yields a weight factor 

that is applied to a State-level IAP area 

or to the individual IAP areas in a State 

that contains multiple IAP areas. Using 

this adjustment factor, the weighted 

distribution of births for education of 

mother (12 years or less, more than 12 

years) by age of child (19–25 months, 

26–35 months) by race/ethnicity of 

mother (Hispanic, non-Hispanic black, 

non-Hispanic white or other) is 

tabulated for each IAP area. These 

weighted counts provide the poststratification control totals for the 

4-quarter period. 

The Nontelephone Adjustment Used 

Between 1994 and 2001: Modified 

Poststratification 

The analysis of the 1992 NHIS 

(described previously) indicated that the 

relationship between telephone 

ownership and the various UTD 

vaccination coverage variables cannot 

completely be accounted for by 

individual-level demographic and 

socioeconomic variables or by 

county-level demographic, socioeconomic, and health-care-related 

variables. This result, in turn, indicated 

that, within the poststratification cells 

developed from the natality data file, the 

UTD vaccination rates differ between 

telephone and nontelephone children. It 

was, therefore, likely that simple 

poststratification would be only partially 

successful in reducing noncoverage bias. 

The poststratification framework, 

however, offered a way to achieve 

additional bias reduction. At a national 

level the NHIS Immunization 

Supplement or NHIS/NIPRCS provided 

estimates of vaccination rates for 

telephone and nontelephone children for 

the various poststratification cells. This 

information was used to split each 

poststratification cell into two subcells: 

one representing UTD children and the 

other representing children who were 

NUTD. Poststratification then was used 

to adjust the weights of the NIS children 

within these subcells. The definition of 

‘‘up to date’’ for the subcells was based 

on the 4:3:1 series from 1994 through 

Q3/1997–Q2/1998 and on the 4:3:1:3 

series from Q4/1997 through Q3/1998 

onward. 

To describe how the poststratification 

totals were obtained for the two subcells 

of poststratification cell g in a given 

IAP area, let Ng denote the total number 

of children in the cell, and let Pg denote 

the proportion of children in the cell 

residing in households with telephones, 

as determined from the most recent U.S. 

census. Then 

NTg = N Pg g 

denotes the number of children in 

telephone households, and 

NTg = Ng – NTg 
denotes the number of children in 

nontelephone households. Let rg denote 

the weighted proportion of NIS children 

in poststratification cell g who are UTD 

(using the nonresponse-adjusted base 

sampling weight). Also, let ρTg and ρTg 

denote the national 4:3:1 (later, 4:3:1:3) 

vaccination coverage rates, as estimated 

from recent NHIS/NIPRCS data, among 

children in telephone and nontelephone 

households whose maternal race/ 

ethnicity is the same as in 

poststratification cell g of the IAP area. 

Then, the estimated number of children 

who are UTD in poststratification cell g 

of the IAP area is 

N(UTD) = NTg rg + NTg (ρTg /ρTg | ) r g g 

and N(NUTD) |g = N – N(UTD) is the 

estimated number of children who 

(UTD) and N

g |g 

are NUTD. N|g |g 

(NUTD) are then 

used as control totals for the UTD and 

NUTD subcells of poststratification cell 

g of the IAP area. Battaglia et al. 

discuss modified poststratification in 

more detail (18). 

The modified-poststratification 

approach allows direct use of the 

weights to form vaccination coverage 

proportions and totals for each IAP area. 

It has some limitations, however. First, 

to avoid complications, it uses only one 

NHIS vaccination variable: the 4:3:1 

series (replaced by 4:3:1:3 starting with 

Q4/1997–Q3/1998). This approach 

assumes that other measures, such as 

Hep B and VRC, exhibit a strong 

positive correlation with 4:3:1 (or 

4:3:1:3). Second, the modifiedpoststratification technique applies 

national NHIS rates (by maternal 

race/ethnicity) to each individual IAP 

area. Thus, in using the ratio of the 

national UTD rates for nontelephone to 

telephone children, it implicitly assumes 

that the actual ratio is close to this value 

in all IAP areas. Third, poststratification 

is based on the assumption that the 

population control totals are subject to 

little, if any, sampling variability. 

Fourth, the adjustment relies on a 

separate independent survey, NHIS/ 

Series 2, No. 138 [ Page 17 

households with interruptions was closer 

to the estimates for the two 

nontelephone groups than was the 

estimate for persons in telephone 

households without interruptions. 

Questions on whether the household 

experienced an interruption in telephone 

service of 1 week or longer in the past 

12 months were added to the RDD 

interview. The responses make it 

possible to classify children who have a 

completed household interview 

according to whether their household 

experienced an interruption in telephone 

service. 

The notation in table E gives the 

result of cross-classifying the target 

population by telephone status and 

interruption status. The adjustment uses 

two population control totals derived 

from the number of age-eligible children 

in telephone households (NT+), the 

number of such children in nontelephone households (NT+), and the 

estimated number of children from 

households with interruptions in 

telephone service (N|TI). The weights of 

all sample children in households 

without interruptions are adjusted so that 

their sum equals NT+ – N|TI. Similarly, 

the weights of the children in 

households with interruptions are made 

to sum to NT+ + N|TI. 

Similar to modified poststratification (described above), NT+ and NT+ 

arise from allocating the total number of 

age-eligible children in the IAP area 

(derived from NCHS natality data) 

according to the proportion of children 

1–3 years of age in the IAP area who 

reside in telephone households. The 

estimates of that proportion for the IAP 

areas came from an analysis that 

combined the 24 monthly samples from 

the CPS’s Basic Monthly Survey 

(http://ferret.bls.census.gov) for 1996 

and 1997. Table F gives instructions for 

downloading those files. (For each State 

Table E. Notation for numbers in the target population at the time of the telephone survey 

by the combination of telephone status and interruption status 

Interruption status 

The 2002 Revision 

To adjust for potential bias in 

estimated coverage rates that may be 

incurred by sampling only households 

with telephones, the 2002 revised 

method uses data that are specific to the 

IAP area instead of using the same 

adjustment for every IAP area (based on 

recent national data from the NHIS). It 

builds on empirical evidence suggesting 

that households that have experienced a 

recent interruption in telephone service 

are similar to households that do not 

have telephones (35). Using NHIS data, 

Srinath et al. found that persons residing 

in households that have experienced a 

recent interruption in telephone service 

are generally more similar to persons in 

households that do not have telephones 

than are persons in telephone households that have had no interruption, with 

respect to insurance status, self-reported 

health status, Medicaid eligibility, and 

not receiving health care because of its 

cost (36). Table 9 shows how these four 

health-related variables are related to the 

combination of telephone status and 

interruption status in nine large States. 

When combined, telephone status and 

interruption status form four groups of 

households (and persons): those without 

telephone service at the time of the 

survey that had had telephone service 

during the previous 12 months, those 

without telephone service at the time of 

the survey that had not had telephone 

service any time during the previous 12 

months, those with telephone service at 

the time of the survey that had had an 

interruption lasting 1 week or longer 

during the previous 12 months, and 

those with telephone service at the time 

of the survey and throughout the 

previous 12 months. For the majority of 

the 36 combinations of health-related 

variable and State, the prevalence 

estimate for persons in telephone 

NIPRCS, which ended in 2000. For all Telephone status Interruption (I) No interruption (I) Total 

of these reasons a new adjustment for 

noncoverage of households without Telephone (T) ......... NTI NTI NT+

NTI NTI NT+ telephones was implemented in 2002. No telephone (T ) .......

Total ............... N+I N+ I N++
Page 18 [ Series 2, No. 138 

Table F. Instructions for downloading Current Population Survey monthly survey data files partial responders are distributed 

Step Action 

1 Visit the Bureau of Labor Statistics Web site at http://ferret.bls.census.gov. 

2 Click on Get Ferrett Data. 

3 Download the install file for the latest application version of DataFerrett. 

4 After installation is complete, double-click on the DataFerrett application to start the program. 

5 Enter your e-mail address. 

6 Select CPS Basic. 

7 Indicate the month and year of the data file to be downloaded. 

8 List the variables to include in the download of the data.1 

9 Specify the creation of an ASCII file for downloading. 

10 Select a record format. 

11 Download the data file. 

proportionally among the complete 

responders (by dividing the RDD 

weights of complete respondents by the 

weighted response rate). 

Step 4: Rake.The nontelephoneadjusted RDD weights, as adjusted for 

partial nonresponse in Step 3, are 

subsequently raked (as described in 

‘‘Raking the Adjusted Sampling Weights 

of Complete Responders’’). 

The validity of the current 

1For the analysis of telephone coverage, the chosen variables were GESTFIPS (FIPS State code), GTCO (FIPS county code), 

GTMSA (Metropolitan Statistical Area code), HETELHHD (household telephone in living quarters), PRTAGE (age in years), and 

PWSSWGT (weight: second-stage weight). 

and for four urban IAP areas the 

combined CPS sample was large enough 

to support a separate estimate. For the 

other urban IAP areas the estimate was 

derived from a combination of 

MSA-level and State-level samples.) 

The NIS sample for the IAP area yields 

the weighted proportion of children 

from households with interruptions, and 

N|TI equals the product of that proportion 

and NT+. 

When the adjustment factor for the 

weights of children in households with 

interruptions (in an IAP area) would 

exceed 3.0 times the adjustment factor 

for the weights of children in 

households without interruptions, that 

ratio is truncated to 3.0. The resulting 

adjusted weights are then poststratified, 

using the control totals for the same 

cells as in simple poststratification. 

Table 10 illustrates the calculations for 

the interruption-based adjustment in the 

Georgia–Rest of State IAP area. 

Using data from the 1997 NHIS, 

Frankel et al. found that, for 12 

health-related variables correlated with 

telephone status, the interruption-based 

adjustment eliminated 76 percent of the 

nontelephone bias that simple 

poststratification was unable to remove 

(35). Using 1997–99 NHIS data for nine 

large States, Srinath et al. found that, for 

four health-related variables, the 

interruption-based adjustment eliminated 

60 percent of that bias (36). 

It is reasonable to expect similar 

reductions in the bias in the NIS. The 

interruption-based approach makes a 

separate adjustment in each IAP area. 

By relying on data on interruptions in 

telephone service, it is less direct than 

modified poststratification, which uses 

ratios (from NHIS/NIPRCS) of 

vaccination coverage among 

nontelephone children to vaccination 

coverage among telephone children. 

Those ratios, however, were available 

only at the national level, and the end of 

NHIS/NIPRCS in 2000 meant that they 

would become increasingly out of date. 

Adjustment for Partial 

Nonresponse—Accounting for 

Children with No Vaccinations 

The 1998–2001 Method for Partial 

Nonresponders 

Once the RDD weights are adjusted 

for nontelephone households, they are 

adjusted further to account for 

differences between complete responders 

and partial responders. This process, 

based on a weighting-class methodology, 

involves four steps: 

Step 1: Estimate response 

propensities. As in ‘‘Adjustment of 

Complete Responders’ RDD Weights,’’ 

for every sampled child with a 

completed RDD interview, the 

national-level logistic regression model 

yields a response propensity for having 

adequate provider data. 

Step 2: Assign children to weighting 

classes. Within each IAP area the 

response propensity of each sampled 

child with a completed RDD interview 

places the child in one of five weighting 

classes, defined by the quintiles of the 

response propensities in that IAP area. 

Step 3: Adjust the nontelephoneadjusted RDD weights. Within each 

weighting class the RDD weights of 

weighting-class method depends upon 

whether, within each weighting class, 

missing data from partial respondents 

are missing at random and observed 

data from complete responders are 

observed at random (21,22,37). Research 

is currently underway by the first author 

to evaluate the plausibility of this 

assumption and to learn how vaccination 

coverage rates might change if partial 

respondents’ missing data were imputed 

using a model that accounts for 

selection bias. 

Adjustment for Children Who Had No 

Vaccinations—Implemented in 2002 

Smith et al. have described the 

epidemiologic importance of children 

who have not received any vaccine 

doses, how their characteristics tend to 

be distinctly different from those of 

other undervaccinated children, and 

where they tend to reside in the United 

States (38). In the NIS children are said 

to be unvaccinated if the household 

respondent reported that the child 

received no vaccinations and the child 

had no vaccination providers, or if all 

providers identified by the household 

reported administering no vaccinations 

to the child. In the NIS sampled 

children with no vaccine doses are few 

(totaling only 111 in 2001), and they 

pose a special challenge in accounting 

for their vaccination status among the 

children whose data are included in the 

estimation of vaccination coverage rates. 

These children’s provider-reported 

vaccination histories are not missing at 

random. Specifically, those vaccination 

histories are missing either because the 

children had no medical providers and 

received no vaccinations or because all 

their medical providers reported 

administering no vaccinations. The 

weighting-class methodology 
implemented in the 1998 NIS 

(‘‘1998–2001 Estimation Methodology’’) 

treated children with no vaccinations as 

if their vaccination status were missing 

at random, rather than recognizing that 

they were NUTD on any vaccine. 

That weighting-class methodology 

is valid only for children whose 

vaccination histories are either missing 

at random or observed at random. 

Because the vaccination histories of 

children with no vaccinations are not 

missing at random, it is not valid to 

overlook their vaccination status, treat 

them as if they did not have a 

provider-reported vaccination history, 

and allow them to be represented by 

complete responders, who are more 

likely to be UTD. Also, because the 

vaccination histories of children with no 

vaccinations are not observed at random, 

it is not valid for these children to 

represent partial responders, who are 

more likely to be UTD. Modifications of 

the 1998–2001 weighting-class 

methodology allowed children with no 

vaccinations to play a proper role in 

accounting for partial nonresponse. 

The revised weighting-class 

methodology accounts for the fact that 

the vaccination status of children with 

no vaccinations is neither missing at 

random nor observed at random. The 

unvaccinated children are set aside in 

the following steps: estimating response 

propensities, assigning children to 

weighting classes, adjusting the weights 

of children with adequate provider data, 

and raking the resulting revised weights. 

The revised method involves four steps: 

Step 1: Revised approach to 

estimating response propensities— 

Sampled children with no vaccinations 

are set aside (for use in Step 4 below), 

and a national-level logistic regression 

model is developed. That model then 

yields estimated response propensities 

for all vaccinated children in the sample. 

Step 2: Assignment to a weighting 

class—Within each IAP area each 

vaccinated sampled child is assigned to 

a weighting class according to the 

quintiles of the estimated response 

propensities in the IAP area. Children 

with no vaccinations are not assigned to 

a weighting class. 

Step 3: Adjusting the nontelephoneadjusted RDD weights—Within each 

weighting class the RDD weights of the 

partial responders are distributed 

proportionally among the vaccinated 

complete responders. 

Step 4: Raking the revised weights 

of complete responders—Children with 

no vaccinations are assigned a weight 

equal to their nontelephone-adjusted 

RDD weight. Within each IAP area the 

revised survey weights of complete 

responders from Step 3 are raked to 

match IAP-area-specific control totals, 

minus the weights of children with no 

vaccinations. This ensures that the totals 

of the raked revised weights of the 

complete responders and the 

nontelephone-adjusted RDD weights of 

the children with no vaccinations match 

IAP area control totals. These sampling 

weights are called ‘‘the partialnonresponse-adjusted sampling weights 

that account for the children with no 

vaccinations.’’ 

Evaluation of the Effect of the 

Two Modifications 

Table 11 lists estimated 2001 

coverage rates for each State, revised to 

account for children with no 

vaccinations and incorporating the 

revised nontelephone adjustment to 

show the combined effect of the two 

modifications. ∆ denotes the difference 

between the revised coverage rate and 

the coverage rate that does not account 

for children with zero vaccinations or 

incorporate the new nontelephone 

adjustment. The differences, ∆, are 

generally small: 90 percent of them are 

between –1.8 and +1.2 percentage 

points, with a median difference of 

–0.3 percentage point. These statistics 

suggest that the combined effect of the 

new nontelephone adjustment and the 

revised weighting-class method yielded 

vaccination coverage rates that were 

close to the 1998–2001 estimation 

methodology, which had neither of these 

modifications. 

Explanation of Unexpected 

Consequences 

Estimated vaccination coverage 

rates might be expected to decrease as a 

result of adjusting more accurately for 

nontelephone households and for 

children with no vaccinations. One 

Series 2, No. 138 [ Page 19 

reason for this is the expectation that 

children living in nontelephone 

households are less likely to be UTD, 

and they are represented by children 

living in households that experienced an 

interruption in telephone service. A 

further reason is the expectation that all 

children with no vaccinations are 

NUTD, and including them in the 

calculations for estimated vaccination 

coverage should decrease rates. 

However, these expectations are not 

borne out for all estimated vaccination 

coverage rates—33 percent of the 

revised coverage estimates in table 11 

are greater than the estimates from the 

1998–2001 methodology. The reasons 

why the revised estimates sometimes 

exceed the original estimates (albeit by 

a very small amount) can be traced to 

unfulfilled assumptions underlying the 

two expectations listed above and the 

number and complexity of the 

adjustments to the survey weights in the 

NIS. 

Empirical research on data from the 

NHIS has shown that, at a national 

level, children living in nontelephone 

households have characteristics that are 

similar to those of children in 

households experiencing an interruption 

in telephone service and that these 

characteristics are associated with being 

NUTD. Among the complete responders 

living in a household with an 

interruption in telephone service, 

70 percent are 4:3:1:3 UTD. This 

percentage varies from State to State 

and can be higher than the 4:3:1:3 UTD 

rate for children in households that did 

not experience an interruption in 

telephone service. Therefore, the impact 

of the revised nontelephone adjustment 

also varies, and it can yield estimated 

rates that are higher than the original 

estimates. 

As an example of unexpected 

results arising from the complexity of 

the NIS methods, in 5 of the 50 States 

and the District of Columbia all sampled 

children had vaccinations (n0=0), and 

estimated vaccination coverage rates 

increased slightly as a result of using 

the revised methodology. This can occur 

because the data of children with no 

vaccinations are not used in the national 

response propensity model. However, 

children with no vaccinations were used 
Page 20 [ Series 2, No. 138 

in estimating the model between 1998 

and 2001, and they were considered to 

have had missing provider data. As a 

consequence, Steps 1 through 4 also 

change. These changes can increase 

estimated coverage rates when the 

estimates obtained from the 2002 

estimation methodology are compared 

with those obtained from the 1998–2001 

estimation methodology. 

In States that have sampled children 

with no vaccinations (n0>0), estimates 

of vaccination coverage also can 

increase slightly. Such children are more 

likely to be white, live in families with 

4 or more children under 18 years of 

age, and have moved from a different 

State. Sampled children with these 

characteristics have lower response 

propensities for having adequate 

provider data and would belong to a 

lower-propensity weighting-class in the 

original weighting-class methodology. It 

is important to recognize that sampled 

children belonging to the low-responsepropensity weighting classes tend to be 

less likely to be UTD. 

When the children with no 

vaccinations are removed from the 

response propensity and weighting-class 

methodology, the resulting weighted 

response rate for low-propensity cells 

increases, compared with what the rate 

would be if unvaccinated children 

remained in the cell and were assumed 

to have no provider data. As a result, 

the adjusted weights are smaller within 

the low-propensity cells. Also, children 

with no vaccinations are retained in the 

data set, and their adjusted weights are 

relatively small because these weights 

are never divided by a weighted 

response rate. As a result, children who 

are NUTD can have smaller adjusted 

sampling weights, compared with the 

weights they would receive in the 

1998–2001 methodology. This can tend 

to increase estimated coverage rates. 

Separating the Contributions of the 

Two Modifications 

Further studies examined the 

separate contributions of the new 

nontelephone adjustment and accounting 

for children with no vaccinations to the 

differences in estimates of vaccination 

coverage for 2001. The first two 

columns of table 12 show the State 

estimate of 4:3:1:3 vaccination coverage 

and its standard error based on the 

1998–2001 estimation methodology, 

which uses modified poststratification 

and does not account for children with 

no vaccinations. Subsequent columns 

show the difference in the estimate 

associated with using only the new 

nontelephone adjustment, only 

accounting for children with no 

vaccinations, accounting for children 

with no vaccinations after making the 

new nontelephone adjustment, and 

combining the two modifications. The 

results are summarized as follows: 

(a) Differences between the 4:3:1:3 

estimate that incorporates the new 

nontelephone adjustment but does 

not account for children with no 

vaccinations and the estimate based 

on the 1998–2001 methodology 

ranged from 2.2 to –2.9 percentage 

points, with an interquartile range of 

1.0 percentage point. Thirty of the 51 

differences were negative. 

(b) Differences between the 4:3:1:3 

estimate that accounts for children 

with no vaccinations but does not 

incorporate the new nontelephone 

adjustment and the estimate based on 

the 1998–2001 methodology ranged 

from 1.4 to –1.1 percentage points, 

with an interquartile range of 

0.6 percentage point. Twenty-nine of 

the differences were negative. 

(c) Overall differences between the 

4:3:1:3 estimate that incorporates the 

new nontelephone adjustment and 

accounts for children with no 

vaccinations and the estimate based 

on the 1998–2001 methodology 

ranged from 1.5 to –3.6 percentage 

points, with an interquartile range of 

1.1 percentage points. Thirty-one of 

the differences were negative. 

(d) The nontelephone adjustment is 

made before the children with no 

vaccinations are incorporated into the 

weight calculations. Differences 

between the 4:3:1:3 estimate that 

incorporates the new nontelephone 

adjustment and accounts for children 

with no vaccinations and the 

estimate based on the new 

nontelephone adjustment but not 

accounting for children with no 

vaccinations ranged from 1.9 

to –1.0 percentage points, with an 

interquartile range of 0.7 percentage 

point. Twenty-nine of the differences 

are negative. 

The overall differences in item (c) 

above are equal to the sum of the 

differences in items (a) and (d). For 34 

States the new nontelephone adjustment 

had a larger impact than did accounting 

for the children with no vaccinations. 

Almost all of the differences in table 12 

are smaller than the standard errors of 

the estimates based on the 1998–2001 

methodology, and many of the 

differences are quite small relative to 

the standard errors. 

A Further Evaluation of the Effect of 

Accounting for Children with No 

Doses on Vaccination Coverage 

Estimates 

To assess the effect of accounting 

for children with no vaccine doses 

(without, at the same time, changing the 

method of compensating for households 

with no telephones), a modification of 

the 1998–2001 estimation methodology 

incorporated only that change. For the 

1995–2002 survey years, table G lists 

the national rates of 4:3:1:3 coverage 

estimated by the 1998–2001 estimation 

methodology and by the modification. 

On the national level, accounting for 

children with no vaccine doses had very 

little effect on the 4:3:1:3 vaccination 

coverage rates. Within IAP areas the 

two coverage estimates also differed 

little. The largest difference (in either 

direction) was commonly 1 to 

2 percentage points (with the isolated 

exception of single IAP areas in 1995 

and 2002). Differences of that 

magnitude are small compared with the 

half-widths of the confidence intervals. 

The NIS estimates published 

between 1995 and 2001 did not account 

for children with no vaccine doses. 

Also, NIS public-use files for survey 

years from 1995 through 2001 did not 

include survey weights that accounted 

for the effect of these children (39). 

Although accounting for unvaccinated 

children has a small effect on estimated 

4:3:1:3 vaccination coverage rates, 

analysts who use the public-use files for 

survey years 1995–2002 to evaluate 

State-level and IAP-area-level trends are 
Series 2, No. 138 [ Page 21 

Table G. Effect on estimated 4:3:1:3 coverage of a modification of the 1998–2001 estimation methodology that only accounted for children 

with no vaccine doses: National Immunization Survey, 1995–2002 

National estimate 

Accounting 

for children 

with no doses 

Not accounting 

for children 

with no doses 

IAP area differences1 

Survey year Percent CI2 Percent CI2 Difference Minimum Maximum 

1995 ................................ 74.2 (±1.2) 73.7 (±1.2) 0.5 –2.0 7.2 

1996 ................................ 76.2 (±1.0) 76.4 (±1.0) –0.2 –1.7 1.6 

1997 ................................ 76.0 (±0.9) 76.2 (±0.9) –0.2 –0.9 1.1 

1998 ................................ 79.1 (±0.9) 79.1 (±0.9) 0.0 –1.1 1.0 

1999 ................................ 78.5 (±0.9) 78.4 (±0.9) 0.1 –0.6 1.2 

2000 ................................ 76.0 (±0.9) 76.2 (±0.9) –0.2 –1.2 1.0 

2001 ................................ 77.1 (±0.9) 77.2 (±0.9) –0.1 –1.1 1.4 

2002 ................................ 77.8 (±0.9) 77.6 (±0.9) 0.2 –1.4 3.2 

1IAP is immunization action plan.

2CI is half-width of 95-percent confidence interval.

NOTE: 4:3:1:3 refers to 4 or more doses of diphtheria and tetanus toxoids and pertussis vaccine (DTP), 3 or more doses of polio vaccine (polio), 1 or more doses of measles-containing vaccine

(MCV), and 3 or more doses of Haemophilus influenzae type b vaccine (Hib).

Table H. Estimated 4:3:1:3 coverage by provider-reported ascertainment status, among children with adequate provider data and two or 

more providers: National Immunization Survey, 1995–2002 

4:3:1:3 status 

Completely ascertained children Incompletely ascertained children 

Survey year Percent CI1 Percent CI1 

1995 .................... 83.5 (±1.8) 65.3 (±3.0) 

1996 .................... 80.6 (±4.4) 65.3 (±2.2) 

1997 .................... 83.2 (±1.7) 64.2 (±3.0) 

1998 .................... 85.4 (±1.4) 69.8 (±3.1) 

1999 .................... 83.1 (±1.6) 70.5 (±3.1) 

2000 .................... 78.8 (±3.4) 66.7 (±3.5) 

2001 .................... 83.3 (±1.8) 68.7 (±2.4) 

2002 .................... 81.0 (±5.1) 70.2 (±2.7) 

1CI is half-width of 95-percent confidence interval.

NOTE: 4:3:1:3 refers to 4 or more doses of diphtheria and tetanus toxoids and pertussis vaccine (DTP), 3 or more doses of polio vaccine (polio), 1 or more doses of measles-containing vaccine

(MCV), and 3 or more doses of Haemophilus influenzae type b vaccine (Hib). 

advised to interpret the results with 

caution. 

Conclusions 

In 19 of the 50 States and the 

District of Columbia vaccination 

coverage rates increase slightly as a 

result of using the revised weightingclass methodology, which accounts 

appropriately for children with no 

vaccinations. Generally, the effect of the 

revised methodology is small, yielding 

estimated vaccination coverage rates that 

are within 1.5 percentage points of the 

original weighting-class estimates. Using 

2001 data IAP-area differences of 

4:3:1:3 coverage between the estimates 

from the 2002 and the estimates from 

the 1998–2001 methodology ranged 

from –3.6 percentage points to 

+1.5 percentage points, with a median 

difference of –0.2 percentage point. 

Evaluation of the Effect of 

Incomplete Ascertainment 

of Provider-reported 

Vaccination Histories on 

Estimates of Vaccination 

Coverage 

Background 

‘‘Trends in Response Rates and Key 

Monitoring Statistics, 1994–2002’’ 

discusses potential limitations of the 

NIS data. One limitation arises from 

children with adequate provider data 

who had two or more vaccination 

providers, some of whom did not 

respond with at least a portion of the 

child’s vaccination history. These 

children have ‘‘incompletely ascertained 

provider-reported vaccination histories.’’ 

Children who had ‘‘completely 

ascertained provider-reported 

vaccination histories’’ are defined as 

those who had two or more vaccination 

providers, all of whom responded to the 

PRC with at least a portion of the 

child’s vaccination history. 

In 2002, 27.5 percent of the 21,317 

children with adequate provider data had 

two or more providers (figure 2). 

Among these 53.1 percent were 

incompletely ascertained. Table H lists 

estimated 4:3:1:3 coverage rates by 

whether a child’s provider-reported 

vaccination history was completely 

ascertained, among children with 

adequate provider data and two or more 

providers. Between 1995 and 2002 the 

national estimated vaccination coverage 

rates for the incompletely ascertained 

children were consistently lower than 

those of the completely ascertained 
Page 22 [ Series 2, No. 138 

children. These differences may be 

attributed to the underestimation of 

national vaccination coverage rates for 

incompletely ascertained children. These 

children may appear to have fewer 

doses than are required to be UTD 

because a fragment of their vaccination 

history documenting the missing doses 

was not reported by providers who did 

not respond to the PRC. 

Table 13 lists the percentage of 

sampled children with adequate provider 

data who were incompletely ascertained 

by race/ethnicity and survey year. For 

Hispanic, non-Hispanic white, and 

non-Hispanic black children, this table 

shows that the percentage of sampled 

children who were incompletely 

ascertained remained stable between 

1995 and 2002. Over this period the 

change in the percentage of 

incompletely ascertained children did 

not differ between Hispanic and 

non-Hispanic white children (p=0.17), or 

between non-Hispanic black and 

non-Hispanic white children (p=0.88), 

and it did not increase or decrease 

significantly for any of these three 

groups (p=0.07). Over this period the 

percentage of incompletely ascertained 

non-Hispanic black children did not 

differ significantly from that of 

non-Hispanic whites (p=0.23). However, 

the percentage of incompletely 

ascertained Hispanic children was 

significantly greater than that of 

non-Hispanic white children (p<0.05), 

by approximately 4 percentage points on 

average. 

Methods 

To evaluate the effect of incomplete 

ascertainment on estimates of 4:3:1:3:3 

vaccination coverage, the 2002 

estimation and weighting methodology 

(described in ‘‘Adjustment for Partial 

Nonresponse—Accounting for Children 

with No Vaccinations’’) is compared 

with three alternative estimation 

methodologies. The three alternative 

methodologies differ according to how 

they classify incompletely ascertained 

children as having a sufficiently wellascertained provider-reported 

vaccination history to merit including 

those histories in the estimation of 

vaccination coverage rates. 

For alternative methodology #1 

none of the incompletely ascertained 

children were counted as having a 

sufficiently well-ascertained history. For 

alternative methodology #2 incompletely 

ascertained children who were 4:3:1:3:3 

UTD according to their providerreported histories were counted as being 

sufficiently well-ascertained. Alternative 

methodology #3 counted those 

incompletely ascertained children who 

were either 4:3:1:3:3 UTD according to 

their provider-reported histories or who 

had a shot card that recorded the same 

number of doses as on their available 

provider reports for each of the DTP, 

polio, MCV, Hib, Hep B, and VRC 

vaccines. To estimate vaccination 

coverage rates, each of the three 

alternative estimation methodologies 

used data from children with no vaccine 

doses, children who had only one 

provider, children with two or more 

providers and a completely ascertained 

vaccination history, and children with a 

sufficiently well-ascertained vaccination 

history. 

Across all survey years, having 

more vaccination providers is positively 

and significantly correlated with higher 

vaccination coverage rates among 

complete responders who either had one 

provider or who were completely 

ascertained (p<0.01). Therefore, each of 

the three alternative methodologies was 

designed to redistribute the partialnonresponse-adjusted sampling weights 

(described in ‘‘Adjustment for Partial 

Nonresponse—Accounting for Children 

with No Vaccinations’’) of children with 

two or more vaccination providers and 

an incomplete and insufficiently 

well-ascertained provider-reported 

vaccination history among children who 

are most similar to them with respect to 

their number of providers. Specifically, 

these sampling weights are redistributed 

to children with two or more providers 

who had either a completely ascertained 

or a sufficiently well-ascertained 

provider-reported vaccination history. 

To adjust the partial-nonresponseadjusted sampling weights for 

incomplete ascertainment, each of the 

three alternative methodologies follows 

a four-step approach. This approach is 

similar to the weighting-class 

methodology described in ‘‘Adjustment 

for Partial Nnonresponse—Accounting 

for Children with No Vaccinations’’ that 

yielded partial-nonresponse-adjusted 

sampling weights and accounted for the 

children with no vaccination doses. The 

four steps are: 

Step 1: Estimate predictive 

probabilities—Sampled children with 

one provider or with no vaccinations are 

set aside (for use in Step 4 below). 

From the data of the remaining children 

(those with two or more vaccination 

providers), a national-level logistic 

regression model is developed. The 

binary dependent variable indicates 

which children are sufficiently wellascertained. Using the predictors in 

table C and the variable selection 

procedure described in ‘‘Adjustment of 

Complete Responders’ RDD Weights,’’ 

the model yields an estimated predictive 

probability of having a sufficiently well 

ascertained provider-reported 

vaccination history for each vaccinated 

child with two or more providers. 

Step 2: Assign children to weighting 

classes—Within each IAP area each 

sampled child with two or more 

providers is assigned to one of two 

weighting classes. These weighting 

classes are defined by the median of the 

estimated predictive probabilities in the 

IAP area. Children with only one 

provider or no vaccinations are not 

assigned to a weighting class. 

Step 3: Adjust the weights—Within 

each weighting class the sampling 

weights of the children with 

insufficiently well-ascertained histories 

are distributed proportionally among the 

children with a sufficiently wellascertained history. The median and 

inter-quartile range of the adjusted 

weights are determined, along with a 

limit equal to the median plus 4 times 

the inter-quartile range. Adjusted 

weights that exceed the limit are 

trimmed to equal the limit. 

Step 4: Rake the revised weights of 

the children with a sufficiently 

well-ascertained provider-reported 

vaccination history—Children who were 

complete responders with one provider 

and children with no vaccinations retain 

their partial-nonresponse-adjusted 

sampling weights. Within each IAP area 

the sampling weights from Step 3 of 

children with a sufficiently well­
Series 2, No. 138 [ Page 23 

ascertained vaccination history are raked 

using the variables in table D to match 

IAP-area-specific control totals, minus 

the weights of children who were 

complete responders with one provider 

and the weights of children with no 

vaccinations. This process ensures that 

the raked sampling weights of the 

sufficiently well-ascertained children, 

the sampling weights of complete 

responders with one provider, and the 

sampling weights of children with no 

vaccination history match the 

IAP-area-specific control totals for the 

variables in table D. 

When raking failed to converge, the 

raking variable in table D with the 

largest discrepancy between the last 

iteration and the next-to-last iteration 

(excluding the adjustment cell, adj.cell) 

was removed from the list of raking 

variables. Raking was then restarted, 

and the procedure was repeated until 

raking converged. 

Results 

Using data from the 2002 NIS 

table 14 lists the 4:3:1:3:3 coverage 

estimate for each State and the District 

of Columbia using the 2002 

methodology and the three alternative 

methodologies, along with the difference 

between the estimates from each of the 

three alternative methodologies and the 

estimate from the 2002 methodology. 

These differences suggest that the 2002 

national 4:3:1:3:3 vaccination coverage 

rate may be underestimated between 

1.6 percentage points and 4.3 percentage 

points because of incompletely 

ascertained provider-reported 

vaccination histories. 

Figures 3–5 plot the difference 

between each alternative methodology’s 

4:3:1:3:3 estimate and the 2002 

estimation methodology’s estimate, 

versus the 2002 estimation 

methodology’s estimate. On the State 

level, adjustment for underascertainment may result in an increase 

in the estimated 4:3:1:3:3 coverage rate 

by as much as 10.3 percentage points or 

a decrease by as much as 1.6 percentage 

points across the three alternative 

methodologies. Further, the potential 

bias attributable to underascertainment 

does not depend on the estimate 

Figure 3. Plot of estimated difference in vaccination coverage between alternative 

methodology #1 and the 2002 estimation methodology versus the 4:3:1:3:3 estimates 

obtained from the 2002 estimation methodology: National Immunization Survey, 2002 

obtained using the 2002 estimation and 

weighting methodology. 

Discussion 

The alternative methodologies 

described in ‘‘Methods’’ are based on 

adjusting the NIS partial-nonresponseadjusted sampling weights (that account 

for the children with no vaccinations) of 

children who have two or more 

vaccination providers. Within each IAP 

area sampled children with two or more 

providers who have an insufficiently 

well-ascertained vaccination history are 

treated as if they have a missing 

vaccination history. Their partialnonresponse-adjusted sampling weights 

are redistributed among other sampled 

children who have two or more 

vaccination providers and a sufficiently 

well-ascertained provider-reported 

vaccination history. Furthermore, the 

sampling weights of children with an 

insufficiently well-ascertained 

provider-reported vaccination history are 

redistributed among children who have a 

sufficiently well-ascertained providerreported vaccination history and are 

similar to them with respect to their 

estimated probability of having a 

sufficiently well-ascertained providerreported vaccination history. No portion 

of these survey weights is distributed to 

complete responders who either have 

one vaccination provider or have had no 

vaccinations. The latter two groups of 

children have zero probability of being 

incompletely ascertained and, thus, are 

not comparable in this important respect 

to any children with two or more 

providers, all of whom had a positive 

probability of being incompletely 

ascertained. Further, because the number 

of providers is known to be positively 

correlated with a greater chance of 

being UTD, both the bias and variance 

of vaccination coverage estimates will 

be reduced by redistributing these 

survey weights among other children 

who have the same important predictors 

of vaccination coverage. 
Page 24 [ Series 2, No. 138 

vaccination history but whose 

provider-reported history was validated 

as being complete from a householdmaintained record of the child’s history. 

As a result, the correction for the bias 

that may be attributed to incomplete 

provider-reported vaccination histories is 

more modest: 3.8 percentage points. 

However, 71.8 percent of the sampled 

children discarded by alternative 

methodology #1 are retained. These 

children are more likely to belong to a 

racial and/or ethnic minority (table 4) or 

have other characteristics that are 

important in other epidemiologic 

analyses. Although the percentage of 

incompletely ascertained children whose 

household reported vaccination histories 

using a shot card varied greatly from 

State to State (figure 6), the correction 

in ascertainment bias from alternative 

methodology #3 did not depend on this 

percentage (figure 7). Thus, the extent of 

the bias correction using alternative 

methodology #3 did not vary from State 

to State in a manner that depended on 

an important predictor of being UTD. 

Further, use of the shot card in 

alternative methodology #3 tends to 

decrease this method’s estimate of 

vaccination coverage—children whose 

data are included in the estimation of 

vaccination coverage as a result of 

validating existing reports with a shot 

card are NUTD. Thus, alternative 

methodology #3 may be viewed as an 

attempt to include more data from the 

sample in the vaccination coverage 

estimate, at the expense of obtaining a 

somewhat more conservative correction 

to potential ascertainment bias than is 

obtained from alternative #2. 

Among children with two or more 

providers national coverage estimates 

for incompletely ascertained children 

were consistently lower between 1995 

and 2002 than for completely 

ascertained children. These differences 

may be attributed to the underestimation 

of national vaccination coverage rates 

for incompletely ascertained children, 

who appear to have fewer doses than 

required to be UTD, because a fragment 

of their vaccination history documenting 

the missing doses was not reported by 

some of their providers who did not 

respond to the PRC. On the national 

level all three alternative estimation 

Figure 4. Plot of estimated difference in vaccination coverage between alternative 

methodology #2 and the 2002 estimation methodology versus the 4:3:1:3:3 estimates 

obtained from the 2002 method: National Immunization Survey, 2002 

If, within each weighting class, the 

missing portions of incompletely 

ascertained provider-reported 

vaccination histories are missing at 

random, then vaccination coverage 

estimates obtained from alternative 

methodology #1 would nearly eliminate 

bias attributable to incomplete 

provider-reported vaccination histories. 

Results from alternative methodology #1 

suggest that the official estimate of the 

national 4:3:1:3:3 vaccination coverage 

rate for 2002 may be low by as much as 

5.7 percentage points (table 14). An 

important disadvantage of this 

alternative methodology is that, in 2002, 

incompletely ascertained providerreported vaccination histories from 

3,106 sampled children are discarded. 

This corresponds to 14.6 percent of the 

sample of complete responders. 

Incompletely ascertained children are 

more likely to be Hispanic than 

non-Hispanic white, or to have other 

characteristics traditionally associated 

with being NUTD (table 4). Because of 

this it may be more appealing to use 

one of the other alternative 

methodologies, which retain more of 

these children in the sample. 

Alternative methodology #2 retained 

2,120 additional cases because they 

were 4:3:1:3:3 UTD according to 

available provider reports. Using this 

method the correction for the bias that 

may be attributed to incomplete 

provider-reported vaccination histories is 

4.3 percentage points. This alternative 

methodology may lack credibility and 

may be easily criticized as being biased 

because it includes only UTD cases 

among those with an incompletely 

ascertained vaccination history. This 

methodology may be perceived as an 

attempt to slant the data to achieve 

higher estimates of vaccination 

coverage. 

Alternative methodology #3 

balances the UTD cases included by 

alternative #2 by including NUTD 

children who have an incompletely 

ascertained provider-reported 
Series 2, No. 138 [ Page 25 

Figure 5. Plot of estimated difference in vaccination coverage between alternative 

methodology #3 and the 2002 estimation methodology versus the 4:3:1:3:3 estimates 

obtained from the 2002 method: National Immunization Survey, 2002 

methodologies yielded a higher estimate 

of the national 4:3:1:3:3 coverage rate, 

and, thus, provided a correction to the 

underestimation of vaccination coverage 

resulting from incomplete ascertainment. 

However, on the State level alternative 

method #1 may produce an estimate that 

is lower than the estimate obtained 

using the 2002 weighting and estimation 

methodology. This can happen because 

characteristics associated with being 

incompletely ascertained (table 4) are 

similar to the characteristics that are 

known to be associated with being 

NUTD. States with larger proportions of 

children who have characteristics 

associated with being NUTD have more 

children who are incompletely 

ascertained and are represented in the 

weighting class by completely 

ascertained children who are less likely 

to be UTD. Using the weighting-class 

methodology described in ‘‘Methods,’’ 

the partial-nonresponse-adjusted 

sampling weights of sufficiently 

well-ascertained children in this 

weighting class will be increased and 

may lead to an adjusted estimate that is 

lower than the unadjusted estimate. 

None of the three alternative 

methodologies were used in 2002 to 

adjust official estimates for incomplete 

ascertainment. 

The First Three 

Topical Modules, 

2001 

The NIS was undertaken to 

monitor vaccination coverage on 

an ongoing basis. Besides 

estimated coverage rates for IAP areas, 

additional information would assist the 

NIP in improving vaccination coverage 

rates. Specific topics include health 

insurance and parents’ ability to pay for 

vaccinations; parental knowledge and 

experiences about immunization; and 

daycare arrangements, breastfeeding 

practices, and WIC participation. Data 

on these important topics were collected 

and are being analyzed to improve 

understanding of vaccination in the 

United States This information could 

contribute to further increases in 

vaccination rates. 

The need to collect information on 

these topics was carefully balanced with 

the burden that respondents bear in 

participating in the RDD interview. 

Approximately 85 percent of 

respondents are mothers with at least 

one child between 19 and 35 months of 

age. Also, the average length for the 

household interview is approximately 24 

minutes for households with an 

age-eligible child. Although the need for 

information on additional topics is great, 

if all respondents were asked additional 

questions, the NIS interview would 

become considerably longer and more 

burdensome. 

To control respondent burden, a 

split-sampling design is used. Each 

household with an age-eligible child is 

randomly assigned to receive a module 

of questions pertaining to only one of 

the three topics (a topical module). The 

overall goal of the split-sampling design 

is to control interview time with 

respondents and yet enhance the NIS 

interview by collecting additional 

analytically important information. 

To make room for the new 

topical-module questions and ensure that 

the overall household burden does not 

increase unduly, several questions that 

had been administered to all respondents 

were dropped. Specifically, detailed 

questions on participation in the WIC 

program and the age of the child during 

WIC participation were no longer asked 

of all respondents. Also dropped were 

two questions on the parent or 

guardian’s perception of whether their 

child is UTD on recommended 

vaccinations and identifying who took 

the child for most of his or her 

vaccinations. 

The first three modules were 

introduced into the NIS in Q3/2001 and 

were originally scheduled to be asked 

for four consecutive quarters (Q3/2001– 
Page 26 [ Series 2, No. 138 

Figure 6. Percentage of incompletely ascertained children whose parent reported vaccination histories using a shot card by State: National 

Immunization Survey, 2002 

Q2/2002). (Ultimately, they were among national health surveys. Adding This section describes: 

continued for two additional quarters, 

Q3–Q4/2002.) These modules may be 

repeated, or they may be replaced with 

other modules as new topics are 

proposed for study. The rapid 

availability of quarterly data on a 

national level and 4-quarter data at the 

IAP-area level makes the NIS unique 

topical modules to the NIS makes 

information on current events rapidly 

available and increases the pool of data 

on behavioral, social, demographic, and 

economic correlates of vaccination 

practices. Smith et al. provide further 

details on the objectives and design of 

the first three topical modules (40). 

+ The primary analytic purpose of 

each topical module. 

+ Methodological issues for topical 

modules. 

+ The design used to ensure that the 

statistics obtained from each module 

will be suitably precise for the 

module’s primary analytic purpose. 
Series 2, No. 138 [ Page 27 

Figure 7. Difference between the 2002 methodology and estimation method #3 versus the 

percentage of incompletely ascertained children in the sample who had a shot card from 

which household-reported vaccination histories were obtained during the National 

Immunization Survey random-digit-dialed interview: National Immunization Survey, 2002 

Analytic Objectives 

This section describes the objectives 

of the first three modules. 

Health Insurance and Ability to 

Pay for Vaccinations 

This module is referred to as the 

HIM. 

Costs to parents and providers are a 

known barrier to vaccination. 

Specifically, administration of vaccines 

by private providers depends on 

insurance reimbursement rates, the 

availability of publicly purchased 

vaccines, and other possible costs to 

providers. Referral of children needing 

vaccinations away from a child’s 

medical home to a health department 

clinic also depends on insurance 

coverage and out-of-pocket costs to 

parents. These referrals cause missed 

opportunities and delays in timely 

vaccinations. Data from this topical 

module provide information on these 

economic and health insurance-related 

barriers to vaccination and their impact 

on vaccination coverage levels. 

VFC is a federal entitlement 

program that provides publiclypurchased vaccines for four groups of 

children: uninsured children, 

underinsured children if they go to a 

federally qualified health center, 

Medicaid-eligible children, and 

American Indian or Alaska Native 

children. Nationally approximately 

32 percent of preschool children are 

eligible for VFC. To correctly distribute 

the VFC funds to the States, CDC needs 

to know the proportion of a State’s 

preschool children who are entitled to 

VFC vaccine. This module yields 

State-by-State estimates of this 

proportion, and these estimates can be 

combined with State program 

information to distribute funds. 

Although VFC is a federal program, 

it is operated at the State level. Each 

State enrolls providers in the program, 

and these providers administer VFC 

vaccine to eligible children. Because the 

NIS provider survey asks whether the 

provider is enrolled in VFC, this module 

allows each State to determine the 

proportion of VFC-eligible children who 

receive their vaccines from VFCenrolled providers. This information will 

help guide States’ provider-enrollment 

efforts. 

In 2001 health departments purchased 

vaccines using one of five policies: 

+ Universal—all recommended vaccines 

were purchased for all children. 

+ Universal select—selected vaccines 

were purchased for all children. 

+ VFC and underinsured—all 

recommended vaccines were 

purchased for VFC-eligible and 

underinsured children. 

+ VFC and underinsured select— 

selected vaccines were purchased for 

VFC-eligible and underinsured 

children. 

+ VFC only—selected vaccines were 

purchased only for VFC-eligible 

children. 

This module can show whether the 

likelihood of referral to health 

department clinics is associated with 

vaccine purchase policy. 

As mentioned above, an important 

group of children are eligible for VFC 

by virtue of being eligible for Medicaid. 

The eligibility of these children is based 

on their income-to-poverty ratio, in 

which the numerator is the family 

income (in the past calendar year) and 

the denominator is the U.S. Census 

Bureau poverty threshold (for that 

calendar year) for the size of the family 

and the number of children under 18 

years old in the household who are 

related to the child. For children in the 

NIS the family income, family size, and 

number of related children come from 

the RDD interview. 

Parental Knowledge and 

Experiences 

This module is referred to as the 

PKM. 

Factors that are believed to 

influence a child’s UTD vaccination 

status include: 

+ Parental perception of vaccine 

safety. 

+ Perception of vaccine efficacy. 
Page 28 [ Series 2, No. 138 

+ Awareness of the recommended 

vaccination schedule. 

+ Perception of the need for vaccines 

(i.e., the severity and probability of 

exposure to vaccine-preventable 

diseases). 

Also, important influences (e.g., 

doctors, vaccination campaigns directed 

toward families) may affect parental 

decisions to seek or avoid vaccines. 

Understanding these influences is 

important in developing new initiatives 

and in improving current vaccination 

programs. 

The questions in this topical module 

aim to assess the parent or guardian’s 

perceptions about vaccine safety and 

influences to seek vaccines. The 

relationship between these perceptions 

and a child’s timely receipt of vaccines 

also will be evaluated. A better 

understanding of these factors will 

enable the NIP to address concerns and 

improve education, with the overall goal 

of increasing timely vaccination 

coverage among young children in the 

United States. 

Daycare, Breastfeeding, and 

WIC 

This module is referred to as the 

DCM. 

Young children in daycare facilities 

are at greater risk of disease because of 

the increased chance of exposure to 

vaccine-preventable diseases. Thus, 

some States require that children 

attending licensed daycare facilities 

receive vaccinations. Parents of young 

children in daycare may be informed by 

their daycare facility about the 

importance of immunization, even if 

vaccines are not mandatory for 

enrollment. 

One goal of the Healthy People 

2010 is to increase UTD vaccination 

rates among children attending 

daycare (3). Questions in this module 

allow NIP to evaluate the extent of 

attendance in daycare and to analyze 

vaccination coverage as it relates to 

attendance. 

Breastfeeding is believed to give 

children antibodies and other factors that 

help protect against invasive forms of 

some diseases, such as Haemophilus 

influenzae type b. However, some 

parents may think breastfeeding lessens 

the need for timely vaccinations. 

Knowledge of the prevalence of 

breastfeeding in the United States and 

whether it is linked to vaccination status 

is important for maternal and child 

health programs to plan and improve 

campaigns to increase this healthful 

practice while maintaining high 

age-appropriate vaccination coverage. 

The NIP routinely assesses whether 

the WIC program encourages mothers to 

adequately vaccinate their children. The 

WIC program was established to 

provide education and access to 

nutritious diets to low-income children 

and pregnant and lactating women at 

high risk for inadequate diets. This 

program serves about 5.5 million infants 

and children. Almost one-half of the 

babies born in the United States qualify 

for WIC. In 1997 the WIC program 

began an initiative to promote 

breastfeeding. Despite its efforts and 

relative success in increasing 

breastfeeding, WIC supplies formula to 

mothers and may be creating an 

unintentional disincentive to 

breastfeeding. Analysis of data on 

daycare, breastfeeding, and WIC 

participation from the same sample of 

children allows the study of potentially 

complex relationships among UTD 

vaccination status and daycare 

attendance, WIC participation, and 

breastfeeding practices. 

The Design for the First 

Three Topical Modules 

The split-sampling design for the 

initial four quarters (Q3/2001–Q2/2002) 

randomized each completed RDD 

interview to receive only one of the 

three topical modules: health insurance 

and ability to pay for vaccinations 

(HIM); parental knowledge and 

experiences (PKM); or daycare 

arrangements, breastfeeding practices, 

and WIC (DCM). To obtain suitably 

precise estimates for the primary 

analytic objectives of each topical 

module, the design allocated 

approximately 74.6 percent of the 

sample to HIM, 12.7 percent to PKM, 

and 12.7 percent to DCM. The sample 

for each module was allocated equally 

to the 78 IAP areas. The following 

subsections give further details about the 

sample design. ‘‘Weighting 

Methodology for Topical Modules’’ 

reports on the numbers of children who 

were randomized to a module and 

whose household completed the module 

interview. 

The Daycare, Breastfeeding 

Practices, and WIC Module 

The estimated sample size for this 

module was based on the objective of 

producing suitably accurate national 

coverage estimates for population 

subdomains that make up at least 

50 percent of the entire population. 

These subdomains include children 

enrolled in daycare (~54 percent), 

children who were breastfed 

(~60 percent), and children who ever 

participated in the WIC program 

(~51 percent). For these purposes the 

term ‘‘suitably accurate’’ refers to 

estimates that are within 2.5 percentage 

points of the true but unknown national 

coverage with a probability of 0.95 

when the true coverage is 80 percent 

within a subdomain that makes up 

50 percent of the target population. 

Among the roughly 34,000 

completed interviews expected over the 

initial 4-quarter period, approximately 

4,300 (12.7 percent) were allocated to 

DCM. Adequate provider data are 

obtained for approximately 67 percent of 

children who complete the RDD survey. 

The number of children with adequate 

provider data for DCM was, therefore, 

expected to be around 2,900 over the 

4-quarter period. For a subdomain that 

makes up 50 percent of the target 

population, this sample would yield 

approximately 1,450 children with 

provider-reported vaccination histories. 

Using these specifications and the 

average expected design effect of 1.52 

for estimated national vaccination rates 

in the NIS, the effective sample size 

was approximately 950 children in the 

subdomain of interest (40). Table J 

shows that, with these design 

specifications, the expected half-width 

of the 95-percent confidence interval 

would be approximately 2.5 percentage 

points. 
The Parental Knowledge and 

Experiences Module 

Among the 34,000 completed 

interviews expected over the initial 

4-quarter period, approximately 4,300 

(12.7 percent) completed household 

interviews were allocated to PKM. 

Subdomains for this module were 

expected to range from 5 percent to 

50 percent of sample households. Table J 

shows the expected 95-percent 

confidence interval half-widths for 

estimated national vaccination rates for 

such subdomains. 

The Health Insurance and 

Ability to Pay Module 

The estimated sample size for this 

module was based on the assumption 

that accurate State-level statistics are 

important. The 25,400 completed 

interviews expected for this module 

represent about 74.6 percent of the 

34,000 expected completed interviews 

annually. At the State level the sample 

size was expected to range from 325 to 

1,625 completed interviews, according 

to the number of IAP areas in the State 

(table K). A key estimate from HIM was 

the percentage of children who were 

eligible for the VFC program. About 

32 percent of the children 19–35 months 

of age in a State were expected to be 

eligible for VFC. As a consequence, 

confidence-interval half-widths were 

expected to be in the range of 3.3 to 

5.5 percentage points (table K). Further, 

if the true percentage of VFC-eligible 

children who are UTD on 

immunizations is 80 percent, the 

half-width of the corresponding 

95-percent confidence interval was 

expected to range from 6.7 to 

10.6 percentage points (table K). 

Weighting Methodology 

for Topical Modules 

(Q3/2001–Q2/2002) 

As discussed above, the topical 

modules were implemented in the first 

four quarters by taking all age-eligible 

households that reached the end of the 

NIS interview and randomly assigning 

them to one of the three modules. If a 

Series 2, No. 138 [ Page 29 

Table J. Expected 95-percent confidence interval half-widths for topical modules designed 

to yield national coverage estimates within subdomains of specified size 

Expected half-width of 

Subdomain size 95% confidence interval 

in percent in percentage points 

5 ................................. 8.0 

10 ................................. 5.7 

20 ................................. 4.0 

30 ................................. 3.3 

40 ................................. 2.8 

50 ................................. 2.5 

Table K. State sample sizes and expected 95-percent confidence interval half-widths for the 

health insurance module 

Expected half-width of 95% confidence interval for— 

Number of Number of completed Percent of children Vaccination rate 

IAP areas interviews over eligible for for VFC-eligible 

in State1 four quarters VFC program2 children2 

2VFC is Vaccines for Children, a federal entitlement program that provides publicly-purchased vaccines for certain groups of 

1 ......................

2 ......................

3 ......................

4 ......................

5 ......................

1IAP is immunization action plan. 

325 5.5 10.6 

650 4.6 8.6 

975 4.3 8.1 

1,300 3.5 6.8 

1,625 3.3 6.7 

children. 

household contained two or more 

age-eligible children, all were assigned 

to the same module. The only exception 

to this procedure was for PKM, where 

only the youngest age-eligible child in 

the household was assigned. The 

random assignment was implemented 

separately in each of the 78 IAP areas. 

The children with a completed 

topical-module interview received a 

topical-interview weight that 

incorporates adjustments for interview 

nonresponse. The subset of children 

with completed module interviews who 

have adequate provider data have a 

second weight that incorporates 

adjustments for provider nonresponse. 

Survey Weights for Children 

with Completed Module 

Interviews 

The Q3/2001–Q2/2002 NIS 

completed interviews for 32,587 

children 19–35 months of age. Each of 

these children has an RDD weight that 

reflects adjustments for nonresponse in 

the RDD survey, poststratification to 

population control totals, and an 

adjustment to compensate for the 

exclusion of children residing in 

nontelephone households. Of the 32,587 

children, 28,250 (86.7 percent) were 

randomized to one of the three modules. 

The remaining 4,337 children did not 

reach module randomization. Table L 

traces the children through the stages 

of data collection on the topical 

modules. 

The first step in the weighting 

methodology involved adjusting the 

RDD weights of the 28,250 randomized 

children to account for the children who 

were not randomized. A list of 

demographic and socioeconomic 

categorical variables was assembled, and 

two-variable tables of each variable by 

whether the child was randomized to a 

topical module were examined. Also, 

PROC LOGLINK in SUDAAN was 

used to identify variables that were 

statistically significant at the 0.05 

level (41). Those variables were offered 

in a forward stepwise logistic regression 

using randomization to a topical module 

as the dichotomous outcome variable. 

The Schwarz criterion was used to 

determine the stopping point for the 

stepwise model (42). Table M lists the 

variables offered in the model and the 
Page 30 [ Series 2, No. 138 

Table L. Key indicators for the topical modules: National Immunization Survey, third quarter of 2001 through second quarter of 2002 

Indicator Total HIM1 DCM2 PKM3 

Number of children with NIS interviews .................. 32,587 . . . . . . . . . 

Number of children randomized to topical module ........... 28,250 21,163 3,511 3,576 

Number of module interviews completed ................. 27,843 20,952 3,488 3,403 

Topical module completion rate ....................... 98.6% 99.0% 99.3% 95.2% 

Topical module response rate4 ....................... 64.3% 64.5% 64.7% 62.1% 

Number of children with adequate provider data5 ........... 22,541 16,980 2,797 2,764 

Percent of children with adequate provider data ............ 81.0% 81.0% 80.2% 81.2% 

. . . Category not applicable.

1HIM refers to the health insurance module.

2DCM refers to the daycare arrangements, breastfeeding practices, and WIC participation module. WIC is the Special Supplemental Nutrition Program for Women, Infants, and Children.

3PKM refers to the parental knowledge and experiences about vaccinations module.

4The topical module response rate equals the product of the topical module completion rate, the percentage of children randomized to a topical module (86.7%), and the CASRO (Council of American

Survey Research Organizations) response rate for the National Immunization Survey as a whole (75.2%). See ‘‘Response Rates and Key Monitoring Statistics for 2002.’’

5Number of children with adequate provider data includes 77 unvaccinated children (58 for HIM, 11 for DCM, and 8 for PKM).

variables retained in the final model (in Table M. Logistic regression predictors for randomization to a topical module: National 

the order that they entered the model). Immunization Survey, third quarter of 2001 through second quarter of 2002 

The final logistic regression model 

was used to assign each of the 32,587 

children a predicted probability of being 

randomized to a topical module. As 

described in ‘‘Adjustment of Complete 

Responsers’ RDD Weights,’’ the 

predicted probabilities were ordered 

from lowest to highest value within each 

IAP area, and five approximately 

equal-sized nonresponse weighting 

classes were formed. Within each 

weighting class the RDD weight was 

used to calculate the weighted 

proportion of children randomized to a 

module. The RDD weights of children 

in a given cell who were randomized to 

a module were divided by the weighted 

proportion for that cell to obtain the 

module randomization nonresponseadjusted weight. 

Among the 28,250 children 

assigned to a module 21,163 received 

HIM, 3,511 received DCM, and 3,576 

received PKM (table L). The second 

step in the weighting methodology 

divided the weight calculated in the first 

step by the module subsampling rate: 

0.746 for HIM, 0.127 for DCM, and 

0.127 for PKM. Also at the second step, 

the success of the randomization 

algorithm was examined by testing for 

independence between each 

demographic and socioeconomic 

variable and the module to which the 

child was randomized. The results 

indicated that the module assignment 

operated in a random fashion. 

For a small percentage of the 

children assigned to a module, the 

Variable included 

in final logistic 

Variable description regression model1 

Income-to-poverty ratio ............................... 1

Shot card used during NIS interview ...................... 2

State of residence at birth differs from current State of residence ..... 3

Mother’s education ................................. 4

Relationship of respondent to child ....................... 5

CATI language queue2 ............................... 6

Maternal age group ................................. 3

NI

Race/ethnicity of mother .............................. 3

NI

Number of children in household ......................... 3

NI

Race/ethnicity of child ............................... 3

NI

MSA residence4 ................................... 3

NI

4:3:1:3 up to date according to household report5 .............. 3

NI

Poverty status .................................... 3

NI

Age group of child .................................. 3

NI

Firstborn status of child .............................. 3

NI

1Variables are listed in order of entry.

2CATI is computer-assisted telephone interview.

3NI indicates this variable was not included in the final model.

4MSA is metropolitan statistical area.

5

4:3:1:3 refers to 4 or more doses of diphtheria and tetanus toxoids and pertussis vaccine (DTP), 3 or more doses of polio vaccine 

(polio), 1 or more doses of measles-containing vaccine (MCV), and 3 or more doses of Haemophilus influenzae type b vaccine (Hib). 

module interview was not completed. 

Table J shows the completion rates. The 

third step in the weighting process 

entailed raking the weights of children 

+ The five nonresponse weighting 

classes 

The first three demographic 

variables were used to ensure that the who completed a module to weighted weighted module distribution was the control totals obtained from the same as the NIS distribution. Census Q3/2001–Q2/2002 NIS. region was used to ensure that the The DCM and PKM rakings were weighted geographic distribution for the carried out at the national level and module matched the distribution of NIS included the following variables: children among the four regions. The 

+ Education of mother interruption-in-telephone-service variable 

+ Race/ethnicity of the child was used to maintain the nontelephone 

+ Age group of the child adjustment in the final module interview 

+ Census region weights. Finally, the five nonresponse 

+ Whether the household experienced weighting classes were included in the 

an interruption in telephone service raking to maintain the nonresponse 

of 1 week or longer 
Series 2, No. 138 [ Page 31 

Table N. Logistic regression models for predicting presence of adequate provider data: National Immunization Survey, third quarter of 2001 

through second quarter of 2002 

Variable description1 DCM2 HIM3 PKM4 

Race/ethnicity of the child ............................... 1 5NI 1 

Mother’s education ................................... 2 5

NI 4 

MSA residence6 ..................................... 3 4 5

NI 

State of residence at birth differs from current State of residence ....... 4 2 2 

Poverty status ...................................... 5

NI 5 5NI 

Race/ethnicity of the mother ............................. 5

NI 1 5NI 

Relationship of respondent to the child ....................... 5 3 3 

Household report of 4:3:1:3 up-to-date status ................... 5

NI 7 5NI 

Survey quarter ...................................... 5

NI 6 5NI 

Age group of the mother ................................ 5

NI 5NI 5NI 

Marital status of the mother .............................. 5

NI 5NI 5NI 

Income-to-poverty ratio categories .......................... 5

NI 5NI 5NI 

CATI language queue7 ................................. 5

NI 5NI 5NI 

Number of children in the household ........................ NI NI NI 

1Variables are listed in order of entry for each topical module.

2DCM refers to the daycare arrangements, breastfeeding practices, and WIC participation module. WIC is the Special Supplemental Nutrition Program for Women, Infants, and Children.

3HIM refers to the health insurance module.

4PKM refers to the parental knowledge and experiences about vaccinations module.

5This variable was not included in the final model.

6MSA is metropolitan statistical area.

7CATI is computer-assisted telephone interview.

adjustment for children not randomized 

to a module. 

The HIM raking was carried out at 

the State level. The above six variables 

were used in the raking, along with a 

variable to indicate IAP area within 

State for those States containing two or 

more IAP areas. 

Survey Weights for Children 

with Adequate Provider Data 

Among the 27,843 children with a 

completed module interview 22,464 

(80.7 percent) had adequate provider 

data (table L). Another 77 children (58 

for HIM, 11 for DCM, and 8 for PKM) 

were unvaccinated. Following the 

procedure for 2002 described in 

‘‘Adjustment for Partial Nonresponse— 

Accounting for Children with No 

Vaccinations,’’ the 77 unvaccinated 

children were temporarily set aside. For 

the remaining 27,766 children an 

outcome variable indicated whether the 

child had adequate provider data. PROC 

LOGLINK in SUDAAN was used to 

identify demographic and socioeconomic 

variables that were statistically 

significant at the 0.05 level. 

For each topical module those 

variables were offered in a forward 

stepwise regression to identify the 

predictors to include in the final logistic 

regression model for that topical 

module. The Schwartz criterion was 

used to choose the final model. Table N 

lists the predictors offered and identifies 

the predictors in the final model for 

each module, with order of entry 

indicated. The fitting of separate models 

to the three topical modules is 

equivalent to fitting a single model that 

offers the main effects of the 

demographic and socioeconomic 

predictor variables and the two-factor 

interactions of each predictor variable 

and a topical-module indicator variable. 

For the sake of parsimony, it was 

decided to use the race/ethnicity of the 

child in the final model for HIM, 

instead of race/ethnicity of the mother. 

Of the 16,922 children with completed 

HIM interviews who had adequate 

provider data, 93.9 percent were 

reported to have the same race/ethnicity 

as their mother. 

The predicted probability of having 

adequate provider data was calculated 

for each child. For DCM and PKM the 

predicted probabilities were ordered 

from lowest to highest, and five 

approximately equal-sized nonresponse 

weighting classes were formed at the 

national level. Within each module the 

topical-module interview weights were 

used to calculate the weighted 

proportion of children with adequate 

provider data. The module interview 

weights of the children with adequate 

provider data in each adjustment cell 

were divided by the weighted proportion 

for that cell to obtain the providernonresponse-adjusted weights. 

The final logistic regression model 

for HIM was also used to calculate the 

predicted probability of having adequate 

provider data. Within each IAP area the 

children with a completed HIM were 

ordered from lowest to highest predicted 

probability and then divided into three 

approximately equal-sized groups. For 

each of these weighting classes the 

weighted proportion of children with 

adequate provider data was calculated. 

The HIM module interview weights of 

children with adequate provider data in 

an adjustment cell were divided by the 

weighted proportion for that cell to 

obtain the provider-nonresponse-adjusted 

HIM weight. 

The next step involved raking the 

weights from the prior step to control 

totals from the Q3/2001–Q2/2002 NIS. 

The DCM and PKM rakings were 

conducted at the national level. The 

raking variables for these two modules 

included maternal education, age group 

of child, race/ethnicity of the child, 

census region, whether the household 

experienced an interruption in telephone 

service of 1 week or longer, the five 

nonresponse weighting classes, and the 

provider-reported 4:3:1:3 UTD status of 

the child. In addition the DCM raking 

included a variable from the DCM 

survey indicating whether the child 

attended a daycare center. For the PKM 
Page 32 [ Series 2, No. 138 

raking the additional variable was 

derived from a question rating the safety 

of childhood vaccines. 

The HIM rakings were conducted at 

the State level. The raking variables for 

this module included maternal 

education, age group of child, 

race/ethnicity of the child, whether the 

household experienced an interruption in 

telephone service of 1 week or longer, 

the three nonresponse weighting classes, 

the provider-reported 4:3:1:3 UTD status 

of the child, and an IAP area indicator 

variable for those States with two or 

more IAP areas. For the HIM the 

additional raking variable measured 

whether the child was eligible for the 

VFC program. 

The demographic variables used in 

the raking ensured that the weighted 

distribution of the children with 

adequate provider data for each module 

was the same as in the Q3/2001– 

Q2/2002 NIS. The interruption variable 

was included to ensure that the 

nontelephone adjustment was carried 

through to the final weights. The 

inclusion of the provider-nonresponse 

weighting classes ensured that this 

nonresponse adjustment was maintained. 

The 4:3:1:3 UTD variable was included 

to ensure that the estimate of 4:3:1:3 

UTD vaccination coverage from a 

topical module would be the same as 

that obtained from the Q3/2001–Q2/ 

2002 NIS. Finally, a key subject-matter 

variable from each module was included 

in the raking to ensure that the weighted 

distribution of children with adequate 

provider data on that subject-matter 

variable was the same as the distribution 

for all children who completed that 

module. 

In the final step the unvaccinated 

children who completed a module were 

brought back into the weight-calculation 

process. It was necessary to ratio-adjust 

their module interview weights so that 

the sum of their weights equaled the 

total weighted count of unvaccinated 

children in the Q3/2001–Q2/2002 NIS 

(15,262). 

Two Additional Quarters 

of Topical Modules 

The successful implementation of 

the topical modules prompted their 

continuation for two additional quarters 

of data collection (Q3–Q4/2002). The 

design, however, was modified for those 

two quarters: 13.3 percent of ageeligible households were randomly 

assigned to DCM, 13.3 percent were 

randomized only to PKM, 36.7 percent 

were randomized only to HIM, and 

36.7 percent were randomized to PKM 

and HIM (with the order of 

administration randomly rotated). Thus, 

50.0 percent of households were 

randomized to PKM, and 73.4 percent 

were randomized to HIM. For the six 

quarters combined, table O traces the 

children through the stages of data 

collection (parallel to table L). 

The weighting methodology for the 

six quarters of topical modules data 

collection followed the 4-quarter 

approach. The only notable differences 

were the use of 10 nonresponse 

weighting classes instead of 5 for the 

PKM provider-nonresponse adjustment 

and the use of the 9 census divisions 

rather than the 4 census regions in the 

PKM raking. These modifications were 

introduced because the PKM sample 

size after six quarters increased by 

around 6,500 interviews. 

Future Topical Modules 

The introduction of the three topical 

modules is expected to be the beginning 

of a long-term approach to enhance the 

programmatic value of the NIS and use 

its rapid turnaround capabilities to 

address current questions related to 

vaccination and the health of young 

children. In 2003 two new topical 

modules were administered: vaccine 

shortage and vaccine safety. Both of 

these have been administered again in 

2004, and those who receive the vaccine 

shortage module also receive a module 

on influenza. 

Public-Use Files 

NIS public-use data files for 

1995–2002 are available at 

http://www.cdc.gov/nis/ 

datafiles.htm and on CD–ROM from 

NCHS. Each annual public-use file is in 

ASCII file format and is accompanied 

by a data user’s guide, a code book, and 

SAS input statements for reading the 

ASCII file. Estimates of vaccination 

coverage at the national, State, and IAP 

Table O. Key indicators for the topical modules: National Immunization Survey, third quarter of 2001 through fourth quarter of 2002 

Indicator Total HIM1 DCM2 PKM3 

Number of children with NIS interviews .................. 48,529 . . . . . . . . . 

Number of children randomized to topical module4 .......... 41,937 31,250 5,310 10,393 

Number of children with completed module interviews5 ........ 41,231 30,741 5,273 9,908 

Topical module completion rate ....................... 98.3% 98.4% 99.3% 95.3% 

Topical module response rate6 ....................... 63.4% 63.5% 64.1% 61.5% 

Number of children with adequate provider data7 ........... 32,936 24,596 4,179 7,810 

Percent of children with adequate provider data ............ 79.9% 80.0% 79.3% 78.8% 

. . . Category not applicable. 

1HIM refers to the health insurance module. 

2DCM refers to the daycare arrangements, breastfeeding practices, and WIC participation module. WIC is the Special Supplemental Nutrition Program for Women, Infants, and Children. 

3PKM refers to the parental knowledge and experiences about vaccinations module. 

4In the third and fourth quarters of 2002, 5,016 children were randomized to HIM and PKM. 

5In the third and fourth quarters of 2002, 4,691 children had completed interviews for HIM and PKM. 

6The topical module response rate equals the product of the topical module completion rate, the percentage of children randomized to a topical module (86.4%) and the CASRO (Council of American Survey 

Research Organizations) response rate for the National Immunization Survey as a whole (74.7%). See ‘‘Response Rates and Key Monitoring Statistics for 2002.’’ 

7Number of children with adequate provider data includes unvaccinated children (82 for HIM, 17 for DCM, and 25 for PKM). In the third and fourth quarters of 2002, 3,649 children with completed HIM 

and PKM interviews had adequate provider data. 
area levels are routinely released on the 

Web site (http://www.cdc.gov/nip/ 

coverage) and in the CDC’s Morbidity

and Mortality Weekly Report (MMWR). 

To ensure the highest quality of the 

NIS data, the survey staff uses a wide 

range of quality control procedures at 

every stage of data collection. Khare et 

al. and the National Immunization 

Survey: Guide to Quality Control 

Procedures discuss the quality assurance 

procedures used in the NIS (43–45). All 

information collected in the NIS is 

covered by strict assurances of 

confidentiality and may be used only for 

research purposes. Prior to release the 

contents of each public-use file undergo 

extensive review by the NCHS 

Disclosure Review Board to protect the 

confidentiality of participants and 

data (46). 

An additional resource is the NIS 

Web site at http://www.cdc.gov/nis/ 

reports.htm. The site includes a selected 

bibliography of technical reports 

developed since the inception of the 

survey. 

Summary 

Since it began in 1994 the NIS has 

monitored the performance of its 

methods and investigated potential 

improvements. This report documents 

the changes in sample design and 

estimation methodology adopted through 

2002, and it describes those aspects of 

the NIS as of 2002. It also discusses the 

addition, in 2001, of modules of 

questions on specific topics, following 

the basic household interview, and the 

split-sampling design for allocating 

households among those modules. 

The sample design, in which each 

of the 78 IAP areas is a stratum, has 

undergone one major change. From 

1994 through 1998 it aimed to produce 

an equal number of children with 

completed household interviews in all 

IAP areas. Since 1999 the target has 

been an approximately equal number of 

children with adequate provider data in 

all IAP areas. 

The estimation methodology is 

oriented primarily toward assigning the 

proper sampling weight to each child 

with adequate provider data, as a basis 

for calculating estimates of vaccination 

coverage and estimating their variances. 

The estimation methodology underwent 

one substantial change in 1998 and 

another in 2002. From 1994 through 

1997 each child with a completed 

household interview received a sampling 

weight that included adjustments for 

multiple telephone lines, unit 

nonresponse, and noncoverage of 

nontelephone households. The latter 

adjustment used a modified form of 

poststratification that took into account 

NHIS estimates of a ratio of vaccination 

coverage among nontelephone 

households to vaccination coverage 

among telephone households. A 

two-phase sampling estimator then used 

the resulting RDD weights to estimate 

vaccination coverage for each vaccine 

and series. Within each of five 

categories it calculated the weighted 

proportion of children with provider 

data who were UTD according to their 

providers. Then it combined those 

proportions according to the weighted 

distribution, over the five categories, of 

children with a completed household 

interview. 

The change in 1998 introduced an 

additional sampling weight for children 

with adequate provider data (the 

complete responders). A national model 

was developed using logistic regression 

to estimate each child’s propensity to be 

a complete responder. Within each IAP 

area the quintiles of the distribution of 

these response propensities served to 

define five weighting classes, as a basis 

for adjustment for partial nonresponse. 

A further step produced final weights by 

raking on five demographic variables 

and the weighting classes. This approach 

yields vaccination coverage rates as 

weighted percentages of the complete 

responders. 

The change in 2002 accounted more 

accurately for nontelephone households 

and for unvaccinated children. The 

adjustment for nontelephone households 

built on empirical evidence that 

households that have experienced a 

recent interruption in telephone service 

are often similar to households that do 

not have telephones. It classified RDD 

children according to whether their 

household had had an interruption in 

Series 2, No. 138 [ Page 33 

telephone service and then poststratified 

their weights to two control totals (for 

each IAP area), one for children in 

households without interruptions and the 

other for the sum of children in 

households with interruptions and 

children in nontelephone households. 

Prior to 2002 children who had not 

received any vaccinations were included 

among the partial responders (i.e., their 

provider data were treated as missing at 

random). The 1998 method of adjusting 

for partial nonresponse was modified for 

2002 by setting aside the unvaccinated 

children until the final step and then 

including them with their RDD weights. 

That is, the data of the unvaccinated 

children were not used in estimating 

response propensities, assigning children 

to weighting classes, adjusting the 

weights of complete responders, or 

raking the resulting revised weights. 

An evaluation of the 2002 changes 

applied them to the data from the 2001 

NIS. The differences in the vaccination 

coverage rates for the various vaccines 

and series were generally small. The 

new methods of accounting for 

nontelephone households and 

unvaccinated children yielded 

vaccination coverage rates that were 

close to those produced by the 

1998–2001 methodology. 

By shortening the main household 

questionnaire in 2001 the NIS made 

room for additional questions on 

important topics. To cover more than 

one topic at a time, a split-sampling 

design allocated households with 

completed interviews (in each IAP area) 

among the topical modules; random 

assignment to a module took place after 

completion of the main interview. The 

first three topical modules were 

introduced in Q3/2001 and continued 

through Q4/2002: health insurance and 

ability to pay for vaccinations; parental 

knowledge and experiences; and daycare 

arrangements, breastfeeding practices, 

and WIC. The additional data collection 

went well. Over the six quarters 

86 percent of children with a household 

(NIS) interview were assigned to a 

topical module, and 98 percent of 

those module interviews were 

completed. 
Page 34 [ Series 2, No. 138 

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5. Centers for Disease Control and Alexandria, VA: American Statistical S, Zhao Z. Comparison of NIS and 

Prevention. Notice to readers: Limited Association. 969–74. 1995. NHIS/NIPRCS vaccination coverage 

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6. Smith PJ, Rao JNK, Battaglia MP, et measurement of immunization 31. Massey JT, Botman SL. Weighting 

al. Compensating for provider coverage. Pediatrics 107(1):91–6. 2001. adjustments for random digit dialed 

nonresponse using response 17. Yusuf H, Adams M, Rodewald L, et al. surveys. In: Groves RM, et al., eds. 

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The National Immunization Survey. among providers and parents of New York: John Wiley, 143–60. 1988. 

National Center for Health Statistics. children in selected underserved areas. 32. Brick JM, Burke J. Telephone 

Vital Health Stat 2(133). 2001. Am J Prev Med 23(2):106–12. 2002. undercoverage bias of 14- to 

7. Ezzati-Rice TM, Zell ER, Battaglia MP, 18. Battaglia MP, Malec DJ, Spencer BD, 21-year-olds and 3- to 5-year-olds. 

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668–72. 1995. American Statistical Association. Labor Statistics. Current population 

8. Zell ER, Ezzati-Rice TM, Battaglia MP, 678–83. 1995. survey: Design and methodology. 

Wright RA. National Immunization 19. Cochran WG. Sampling techniques, 3d Technical paper 63. 2000. 

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9. Lepkowski JM. Telephone sampling Med Res 5:215–38. 1996. U.S. Department of Health and Human 

methods in the United States. 21. Rubin DB. Inference and missing data. Services, Public Health Service, 

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et al., eds. Telephone survey 22. Little RJA, Rubin DB. Statistical Prevention, National Center for Health 

methodology. New York: John Wiley, analysis with missing data. New York: Statistics. 1993. 

73–98. 1988. John Wiley. 1987. 35. Frankel MR, Srinath KP, Hoaglin DC, 

10. National Center for Health Statistics. 23. Coronado VG, Maes EF, Rodewald LE, et al. Adjustments for nontelephone 

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Vital Health Stat 2(126). 1999. month-old children in the United 36. Srinath KP, Battaglia MP, Frankel MR, 

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for the 2002 public-use data file. 24. SPlus 2000 user’s guide. Seattle, annual meeting of the American 

http://www.cdc.gov/nis/datafiles.htm. Washington: Data Analysis Products Statistical Association (CD-ROM). 

Division, Mathsoft. Alexandria, VA: American Statistical 

Association. 3323–29. 2002. 
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37. Rubin DB. Multiple imputation for 

nonresponse in surveys. New York: 

John Wiley. 1987. 

38. Smith PJ, Chu SY, Barker LE. Children 

who have received no vaccines: Who 

are they and where do they live? 

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39. National Center for Health Statistics. 

NIS public-use data files, reports and 

publications: Notice to data users. 

Hyattsville, MD: National Center 

for Health Statistics. 2002. 

http://www.cdc.gov/nis/reports.htm. 

40. Smith PJ, Simpson D, Battaglia MP, et 

al. Split sampling design for topical 

modules in the National Immunization 

Survey. 2000 Proceedings of the 

Section on Survey Research Methods. 

Alexandria, VA: American Statistical 

Association. 653–8. 2000. 

41. Research Triangle Institute. SUDAAN 

user’s manual, release 8.0. Research 

Triangle Park, NC: Research Triangle 

Institute. 2001. 

42. Schwarz G. Estimating the dimension 

of a model. Annals of Statistics 

6:461–4. 1978. 

43. Centers for Disease Control and 

Prevention. National Immunization 

Survey: Guide to quality control 

procedures. Section 6.3.1. 2002. 

http://www.cdc.gov/nis/pdfs/qcman.pdf. 

44. Khare M, Battaglia MP, Huggins VJ, et 

al. Accuracy of vaccination dates 

reported by immunization providers in 

the National Immunization Survey. 

2000 Proceedings of the Section on 

Survey Research Methods. Alexandria, 

VA: American Statistical Association. 

665–70. 2000. 

45. Khare M, Battaglia MP, Stokley S, et 

al. Quality of immunization histories 

reported in the National Immunization 

Survey. Proceedings of the international 

conference on quality in official 

statistics (CD-ROM). Stockholm: 

Statistics Sweden. 2001. 

46. Khare M, Battaglia M, Hoaglin DC. 

Procedures to reduce the risk of 

respondent disclosure in a public-use 

data file: The National Immunization 

Survey. In: Proceedings of the Federal 

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2003 Research Conference. 

Washington, DC: Federal Committee on 

Statistical Methodology. 7–12. 2003. 

http://www.fcsm.gov/03papers/ 

Khare_final.pdf. 
Page 36 [ Series 2, No. 138 

Table 1. Number of children 19–35 months of age, by State and immunization action plan area: United States, 2002 

Population Population 

State or IAP area1 in thousands State or IAP area1 in thousands 

Total United States ....................... 5,845 Minnesota ............................. 100 

Alabama .............................. 92 Mississippi ............................ 62 

Rest of State ......................... 78 Missouri .............................. 108 

Jefferson County ....................... 14 Montana .............................. 15 

Alaska ............................... 14 Nebraska ............................. 34 

Arizona .............................. 119 Nevada .............................. 48 

Rest of State ......................... 43 New Hampshire ......................... 21 

Maricopa County ....................... 76 New Jersey ............................ 171 

Arkansas ............................. 54 Rest of State ......................... 164 

California ............................. 774 City of Newark ........................ 7 

Rest of State ......................... 438 New Mexico ........................... 39 

Los Angeles County ..................... 231 New York ............................. 367 

Santa Clara County ..................... 40 Rest of State ......................... 194 

San Diego County ...................... 66 New York City ......................... 173 

Colorado ............................. 90 North Carolina .......................... 173 

Connecticut ............................ 63 North Dakota ........................... 10 

Delaware ............................. 15 Ohio ................................ 220 

District of Columbia ....................... 10 Rest of State ......................... 169 

Florida ............................... 309 Cuyahoga County ...................... 27 

Rest of State ......................... 241 Franklin County ........................ 25 

Duval County ......................... 19 Oklahoma ............................. 72 

Miami-Dade County ..................... 49 Oregon .............................. 67 

Georgia .............................. 191 Pennsylvania ........................... 209 

Rest of State ......................... 155 Rest of State ......................... 178 

Fulton/DeKalb Counties ................... 36 Philadelphia County ..................... 31 

Hawaii ............................... 25 Rhode Island ........................... 18 

Idaho ................................ 29 South Carolina .......................... 83 

Illinois ............................... 267 South Dakota .......................... 15 

Rest of State ......................... 193 Tennessee ............................ 110 

City of Chicago ........................ 73 Rest of State ......................... 77 

Indiana .............................. 126 Shelby County ........................ 21 

Rest of State ......................... 105 Davidson County ....................... 12 

Marion County ........................ 21 Texas ............................... 513 

Iowa ................................ 54 Rest of State ......................... 335 

Kansas .............................. 58 Dallas County ......................... 60 

Kentucky ............................. 79 El Paso County ........................ 20 

Louisiana ............................. 93 City of Houston ........................ 64 

Rest of State ......................... 82 Bexar County ......................... 34 

Orleans Parish ........................ 10 Utah ................................ 63 

Maine ............................... 21 Vermont .............................. 10 

Maryland ............................. 115 Virginia .............................. 148 

Rest of State ......................... 99 Washington ............................ 120 

Baltimore City ......................... 17 Rest of State ......................... 87 

Massachusetts .......................... 116 King County .......................... 33 

Rest of State ......................... 104 West Virginia ........................... 29 

City of Boston ......................... 12 Wisconsin ............................. 101 

Michigan ............................. 195 Rest of State ......................... 79 

Rest of State ......................... 172 Milwaukee County ...................... 22 

City of Detroit ......................... 23 Wyoming ............................. 9 

1IAP is immunization action plan. 

SOURCE: Data were derived from an unpublished natality file for August 2000–December 2001, provided by the Centers for Disease Control and Prevention, National Center for Health Statistics. 
onitoring statistics: National Immunization Survey, 1994–2002 

1994 

(2nd–4th 

tor quarter) 1995 1996 1997 1998 1999 2000 2001 2002 

ed phase 

mbers in released 

1,453,000 1,917,474 2,021,133 2,118,796 2,239,721 2,533,608 2,662,722 3,042,911 3,361,396 

ore CATI1 275,860 407,259 397,276 395,488 407,496 483,903 671,215 1,055,376 1,306,025 

19.0% 21.2% 19.7% 18.7% 18.2% 19.1% 25.2% 34.7% 38.9% 

1,177,140 1,510,215 1,623,857 1,723,308 1,832,225 2,049,705 1,991,507 1,987,535 2,055,371 

- - - 565,194 537,322 573,748 589,944 746,824 1,146,845 1,191,713 1,285,751 

- - - 37.4% 33.1% 33.3% 32.2% 36.4% 57.6% 60.0% 62.6% 

1,374,480 1,851,274 1,905,956 1,950,500 2,024,343 2,243,904 2,345,183 2,641,723 2,849,329 

) 94.6% 96.5% 94.3% 92.1% 90.4% 88.6% 88.1% 86.8% 84.8% 

668,972 885,069 929,066 943,834 945,122 1,009,543 1,014,714 1,054,561 1,056,429 

48.7% 47.8% 48.7% 48.4% 46.7% 45.0% 43.3% 39.9% 37.1% 

eened for presence 

643,328 853,536 899,549 924,328 923,970 979,606 973,784 1,014,363 1,020,404 

ow 7/row 6) 96.2% 96.4% 96.8% 97.9% 97.8% 97.0% 96.0% 96.2% 96.6% 

ble children 617,113 819,825 864,528 889,758 889,489 943,268 937,824 978,378 986,203 

95.9% 96.1% 96.1% 96.3% 96.3% 96.3% 96.3% 96.5% 96.6% 

children 26,215 33,711 35,021 34,570 34,481 36,338 35,960 35,985 34,201 

4.1% 3.9% 3.9% 3.7% 3.7% 3.7% 3.7% 3.5% 3.4% 

children with 

25,017 31,520 32,911 32,434 32,271 33,932 33,477 32,796 30,974 

w 10/row 9) 95.4% 93.5% 94.0% 93.8% 93.6% 93.4% 93.1% 91.1% 90.6% 

5*row 7*row 10)4 86.8% 87.1% 85.8% 84.6% 82.7% 80.3% 78.7% 76.1% 74.2% 

mpleted RDD 

25,247 31,997 33,305 32,742 32,511 34,442 34,087 33,437 31,693 

eck phase 

ed to contact 

- - - - - - - - - 27,169 26,884 28,936 28,402 528,770 527,489 

- - - 684.0% 685.0% 83.0% 82.7% 84.0% 83.3% 86.0% 86.7% 

- - - - - - - - - 34,848 35,429 37,373 37,885 537,268 534,444 

s7 - - - - - - - - - 28,389 33,748 35,517 35,971 532,939 529,579 

- - - 661.0% 676.0% 81.5% 95.3% 95.0% 94.9% 88.4% 85.9% 

der data 7,862 16,183 21,099 22,806 21,827 22,521 22,958 23,531 821,410 

942.5% 50.6% 63.4% 69.7% 67.1% 65.4% 67.4% 70.4% 67.3% 

resolved before CATI (row 2).

rch Organizations.

se numbers were drawn were redefined and revised in 2001.

mmunization Survey provider management database prior to 1997; figures shown are estimated from other sources.

ovider data was revised to include unvaccinated children.

up to date in the household survey were not eligible for provider followup.

Series 2, No. 138 [ Page 37 
Page 38 [ Series 2, No. 138 

Table 3. Factors associated with having two or more vaccination providers, among sampled children with adequate provider data: National 

Immunization Survey, 2002 

Number of Percent at each Percent with two or Relative risk (RR): two or 

Factor and level children factor level (CI1

) more providers (CI1) more providers (CI2) 

Survey quarter

1 ................................ 5,442

2 ................................ 5,458

3 ................................ 5,223

4 ................................ 5,287

25.4 (±0.6) 27.3 (±1.2) 0.9 (0.9, 1.0) 

25.5 (±0.6) 26.9 (±1.2) 0.9 (0.9, 1.0) 

24.4 (±0.6) 26.4 (±1.2) 0.9 (0.8, 1.0) 

24.7 (±0.6) 29.3 (±1.2) (

3

) 

Child’s characteristics 

Race/ethnicity:

Hispanic .......................... 4,194 19.6 (±0.5) 32.2 (±1.4) 1.2 (1.2, 1.3)

Non-Hispanic white .................... 12,940 60.4 (±0.6) 26.5 (±0.8) (

3

)

Non-Hispanic black .................... 2,992 14.0 (±0.4) 25.3 (±1.6) 1.0 (0.9, 1.0)

Non-Hispanic American Indian . . . . . . . . . . . . . 324 1.5 (±0.2) 38.0 (±5.4) 1.4 (1.2, 1.7)

Non-Hispanic Asian . . . . . . . . . . . . . . . . . . . 956 4.5 (±0.3) 22.4 (±2.7) 0.8 (0.7, 1.0)

Non-Hispanic other .................... 4 0.0 (±0.0) 25.0 (±42.4) 0.9 (0.2, 5.2)

Sex: 

Male ............................. 11,024 51.5 (±0.7) 27.3 (±0.8) (

3

) 

Female ........................... 10,386 48.5 (±0.7) 27.6 (±0.9) 1.0 (1.0, 1.1) 

Age: 

19–24 months ....................... 7,766 36.3 (±0.7) 27.2 (±1.0) (

3

) 

25–29 months ....................... 6,340 29.6 (±0.6) 27.2 (±1.1) 1.0 (0.9, 1.1) 

30–35 months 7,304 34.1 (±0.6) 27.9 (±1.0) 1.0 (1.0, 1.1) 

Foreign-born: 

Yes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198 0.9 (±0.1) 38.4 (±6.8) 1.4 (1.2, 1.7) 

No . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21,212 99.1 (±0.1) 27.3 (±0.6) (

3

) 

Mother’s characteristics 

Marital status (or deceased):

Widowed/divorced/separated .............. 1,567 7.3 (±0.4) 31.8 (±2.3) 1.2 (1.1, 1.3)

Never married ....................... 4,070 19.0 (±0.5) 29.1 (±1.4) 1.1 (1.0, 1.2)

Married ........................... 15,759 73.6 (±0.6) 26.6 (±0.7) (

3

)

Deceased ......................... 14 0.1 (±0.0) 28.6 (±23.7) 1.1 (0.5, 2.5)

Educational attainment: 

Less than 12 years .................... 2,626 12.3 (±0.4) 32.2 (±1.8) 1.1 (1.0, 1.2) 

12 years .......................... 6,103 28.5 (±0.6) 28.1 (±1.1) 1.0 (0.9, 1.0) 

More than 12 years, not college graduate ...... 3,986 18.6 (±0.5) 29.2 (±1.4) (

3

) 

College graduate ..................... 8,695 40.6 (±0.7) 24.7 (±0.9) 0.8 (0.8, 0.9) 

Preferred language: 

English ........................... 19,080 89.1 (±0.4) 26.8 (±0.6) (

3

) 

Spanish ........................... 1,995 9.3 (±0.4) 34.7 (±2.1) 1.3 (1.2, 1.4) 

Other ............................ 335 1.6 (±0.2) 18.8 (±4.2) 0.7 (0.6, 0.9) 

Age: 

19 years or under . . . . . . . . . . . . . . . . . . . . 548 2.6 (±0.2) 32.3 (±4.0) 1.4 (1.2, 1.6) 

20–29 years ........................ 8,833 41.3 (±0.7) 33.2 (±1.0) 1.4 (1.4, 1.5) 

30 years or over ..................... 12,029 56.2 (±0.7) 23.0 (±0.8) (

3

) 

Shot card: 

Yes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9,607 44.9 (±0.7) 32.3 (±0.9) (

3

) 

No . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11,803 55.1 (±0.7) 23.5 (±0.8) 0.7 (0.7, 0.8) 

Household characteristics 

Annual income and poverty status:

Above $75,000/year ................... 4,372 20.4 (±0.5) 21.4 (±1.2) (

3

)

Above poverty, $75,000/year or less ......... 11,218 52.4 (±0.7) 29.0 (±0.9) 1.4 (1.3, 1.4)

Below poverty ....................... 3,864 18.0 (±0.5) 31.3 (±1.5) 1.5 (1.4, 1.6)

Unknown .......................... 1,956 9.1 (±0.4) 24.2 (±1.9) 1.1 (1.0, 1.2)

Number of children under 18 years of age living in 

the household: 

1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5,991 28.0 (±0.6) 28.8 (±1.1) (

3

) 

2–3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12,791 59.7 (±0.7) 26.9 (±0.8) 0.9 (0.9, 1.0) 

4 or more ......................... 2,628 12.3 (±0.5) 26.9 (±1.8) 0.9 (0.9, 1.0) 

Moved from another State since child’s birth: 

Moved ........................... 1,733 8.1 (±0.4) 58.6 (±2.4) 2.4 (2.3, 2.5) 

Did not move ....................... 19,607 91.9 (±0.4) 24.7 (±0.6) (

3

) 

MSA:4 

MSA, central city ..................... 9,259 43.2 (±0.6) 26.9 (±0.9) (

3

) 

MSA, not in central city ................. 7,641 35.7 (±0.6) 26.5 (±1.0) 1.0 (0.9, 1.0) 

Non-MSA .......................... 4,510 21.1 (±0.5) 30.0 (±1.4) 1.1 (1.1, 1.2) 

1CI is half-width of 95-percent confidence interval. 2CI is 95-percent confidence interval. 3This is the reference level for this variable. 4MSA is metropolitan statistical area. 
Series 2, No. 138 [ Page 39 

Table 4. Characteristics associated with incomplete ascertainment, among sampled children with two or more vaccination providers and 

adequate provider data: National Immunization Survey, 2002 

Estimated percentage at each level of the characteristic 

p-Value 

Completely ascertained Incompletely ascertained for the 

Characteristic children (CI1

) children (CI1) difference 

Child 

Race/ethnicity:

Hispanic ........................................

Non-Hispanic white ..................................

Non-Hispanic black ..................................

Non-Hispanic American Indian ...........................

Non-Hispanic Asian .................................

Non-Hispanic other ..................................

Sex:

Male ...........................................

Female .........................................

Age:

19–24 months .....................................

25–29 months .....................................

30–35 months .....................................

Foreign-born:

Yes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

No . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Mother 

Marital status (or deceased):

Widowed/divorced/separated ............................

Never married .....................................

Married .........................................

Deceased .......................................

Educational attainment:

Less than 12 years ..................................

12 years ........................................

More than 12 years, not college graduate ....................

College graduate ...................................

Preferred language:

English .........................................

Spanish .........................................

Other ..........................................

Age:

19 years or under ..................................

20–29 years ......................................

30 years or over ...................................

Shot card:

Yes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

No . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Household 

Annual income and poverty status:

Above $75,000/year .................................

Above poverty, $75,000/year or less .......................

Below poverty .....................................

Unknown ........................................

Number of children under 18 years of age living in the household:

1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2–3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4 or more .......................................

MSA:2

MSA, central city ...................................

MSA, not in central city ...............................

Non-MSA ........................................

See footnotes at end of table. 

23.3 (±1.1) 

56.6 (±1.2) 

14.6 (±0.9) 

1.1 (±0.3) 

4.5 (±0.5) 

0.0 (±0.0) 

51.4 (±1.2) 

48.6 (±1.2) 

36.4 (±1.2) 

29.3 (±1.1) 

34.2 (±1.1) 

0.8 (±0.2) 

99.2 (±0.2) 

7.3 (±0.6) 

21.3 (±1.1) 

71.3 (±1.2) 

0.1 (±0.1) 

16.8 (±1.1) 

35.2 (±1.2) 

15.5 (±0.8) 

32.6 (±1.0) 

86.0 (±0.9) 

12.1 (±0.9) 

1.9 (±0.3) 

3.1 (±0.5) 

43.1 (±1.2) 

53.7 (±1.2) 

43.2 (±1.2) 

56.8 (±1.2) 

18.0 (±0.8) 

49.2 (±1.2) 

20.6 (±1.1) 

12.2 (±0.9) 

27.1 (±1.1) 

59.9 (±1.2) 

13.0 (±0.9) 

34.6 (±1.1) 

46.9 (±1.2) 

18.6 (±0.9) 

30.7 (±2.8) <0.01 

50.6 (±2.9) <0.01 

13.8 (±2.1) 0.49 

1.6 (±0.6) 0.12 

3.3 (±1.1) 0.05 

0.0 (±0.0) 0.80 

52.0 (±2.8) 0.68 

48.0 (±2.8) 0.68 

35.0 (±2.7) 0.35 

28.2 (±2.5) 0.41 

36.8 (±2.9) 0.10 

2.5 (±1.0) <0.01 

97.5 (±1.0) <0.10 

8.9 (±1.7) 0.08 

24.1 (±2.5) 0.04 

66.9 (±2.8) <0.01 

0.0 (±0.0) 0.16 

20.8 (±2.6) 0.01 

36.1 (±2.8) 0.55 

16.1 (±1.9) 0.56 

27.1 (±2.3) <0.01 

81.2 (±2.6) <0.01 

17.3 (±2.5) <0.01 

1.5 (±0.7) 0.32 

4.5 (±1.3) 0.07 

53.9 (±2.8) <0.01 

41.6 (±2.8) <0.01 

50.5 (±2.9) <0.01 

49.5 (±2.9) <0.01 

12.6 (±1.6) <0.01 

50.3 (±2.9) 0.46 

24.7 (±2.5) <0.01 

12.4 (±2.3) 0.90 

27.7 (±2.6) 0.66 

59.0 (±2.8) 0.56 

13.3 (±1.9) 0.78 

37.7 (±2.8) 0.04 

45.4 (±2.9) 0.33 

16.9 (±1.9) 0.12 
Page 40 [ Series 2, No. 138 

Table 4. Characteristics associated with incomplete ascertainment, among sampled children with two or more vaccination providers and 

adequate provider data: National Immunization Survey, 2002—Con. 

Estimated percentage at each level of the characteristic 

p-Value 

Completely ascertained Incompletely ascertained for the 

Characteristic children (CI1) children (CI1) difference 

Household—Continued 

Facility type(s) of vaccination provider(s): 

All public ........................................ 62.3 (±1.2) 55.6 (±2.9) <0.01 

All private ....................................... 8.7 (±0.7) 14.2 (±2.1) <0.01 

All hospital ....................................... 14.1 (±0.9) 14.1 (±2.0) 0.99 

All FQHC3 ....................................... 5.7 (±0.6) 6.6 (±1.5) 0.28 

Other .......................................... 9.1 (±0.7) 9.4 (±1.7) 0.75 

Moved from another State since child’s birth: 

Moved ......................................... 6.3 (±0.6) 20.0 (±2.4) <0.01 

Did not move ..................................... 93.3 (±0.6) 80.0 (±2.4) <0.01 

Unknown ........................................ 0.4 (±0.1) 0.0 (±0.0) . . . 

0.0 Quantity more than zero but less than 0.05.

. . . Category not applicable.

1CI is half-width of 95-percent confidence interval.

2MSA is metropolitan statistical area.

3FQHC is federally qualified health center. 
ages of data collection: National Immunization Survey, 2002 

Percentage of 

children Household 

9–35 months old eligibility Eligibility 

in telephone rate benchmark 

households (HER) (EB) 

(1) (2) (3) 

Access Access rate × 

Percentage rate × Percentage completion 

of children completion of children rate × adequate 

Access Access with rate × with provider data 

Ratio of rate Interview rate × adequate adequate complete rate × complete 

HER to EB (column 1 × completion completion provider provider provider provider data 

(HER/EB) column 4) rate rate data data rate response rate 

(4) (5) (6) (7) (8) (9) (10) (11) 

92.8 3.4 4.8 0.7 64.5 90.1 59.9 67.3 39.9 85.4 33.6

91.5 2.893.5 3.0

91.9 3.0

86.3 3.7

94.3 3.588.5 3.8

88.3 3.4

90.1 4.392.6 2.993.5 3.0

90.6 2.3

89.2 2.8

94.9 2.494.2 3.5

95.4 3.394.1 2.8

93.2 2.9

91.5 3.3

89.3 3.5

93.1 2.8

94.4 3.2

87.5 2.5

90.6 4.294.7 3.7

90.6 3.5

87.4 3.3

94.9 3.791.4 4.3

92.1 4.1

93.8 4.0

93.3 3.296.5 3.7

93.3 3.692.3 3.2

94.4 3.5

95.0 3.2

94.2 2.8

88.3 3.1

95.2 3.594.5 3.5

91.8 3.085.3 3.792.6 3.491.0 3.388.4 3.4

4.4 0.6 58.0 88.5 51.3 54.2 27.8 86.2 24.0 4.7 0.6 59.5 91.6 54.5 51.2 27.9 81.3 22.7 

5.6 0.6 50.3 88.6 44.6 62.9 28.1 84.0 23.6 

5.8 0.6 54.9 89.7 49.3 58.2 28.7 80.2 23.0 

6.1 0.6 54.0 89.6 48.4 59.7 28.9 82.1 23.7 

6.2 0.6 54.1 88.3 47.8 60.9 29.1 81.5 23.7 

5.3 0.7 57.1 87.8 50.1 60.6 30.4 86.4 26.2 

5.9 0.7 65.5 92.2 60.4 50.6 30.5 70.5 21.5 

4.4 0.7 61.3 87.1 53.4 58.3 31.1 92.3 28.7 

5.1 0.6 55.8 87.3 48.7 64.6 31.5 83.0 26.1 

3.4 0.7 63.3 86.3 54.6 58.4 31.9 87.2 27.8 

4.3 0.6 57.1 85.1 48.6 66.2 32.2 87.8 28.3 

3.9 0.6 58.5 90.0 52.7 66.2 34.9 89.6 31.2 

5.4 0.7 62.2 90.4 56.2 62.1 34.9 77.8 27.2 

5.3 0.6 59.6 91.5 54.5 64.2 35.0 84.5 29.6 

4.2 0.7 62.7 88.8 55.7 63.5 35.4 87.2 30.8 

4.8 0.6 57.2 87.7 50.2 72.3 36.3 89.5 32.5 

5.1 0.6 58.9 89.6 52.7 68.8 36.3 84.7 30.7 

5.0 0.7 62.8 89.5 56.2 64.7 36.4 86.7 31.5 

4.5 0.6 58.4 90.4 52.8 69.4 36.6 87.8 32.2 

4.9 0.7 61.3 91.3 55.9 65.6 36.7 89.7 32.9 

3.6 0.7 61.9 90.0 55.7 66.2 36.9 83.1 30.6 

5.6 0.8 68.5 91.2 62.5 59.3 37.1 76.3 28.3 

5.3 0.7 66.6 89.7 59.7 62.3 37.2 87.7 32.6 

5.3 0.7 58.8 93.2 54.8 68.8 37.7 86.9 32.8 

4.7 0.7 60.4 93.0 56.2 67.3 37.8 84.9 32.1 

5.5 0.7 63.7 93.2 59.3 63.9 37.9 84.8 32.2 6.0 0.7 65.9 89.3 58.8 64.4 37.9 85.1 32.2 

5.9 0.7 64.8 89.3 57.9 65.4 37.9 83.8 31.7 

5.7 0.7 66.8 91.1 60.9 62.6 38.1 77.2 29.4 

5.0 0.7 60.6 91.1 55.2 69.4 38.3 89.3 34.2 

5.7 0.6 62.1 92.8 57.7 66.6 38.4 85.6 32.9 

5.1 0.7 66.3 89.7 59.5 64.6 38.4 88.4 34.0 

4.7 0.7 63.3 92.3 58.4 66.6 38.9 83.7 32.6 

4.9 0.7 67.6 89.2 60.3 64.6 38.9 85.0 33.1 

4.6 0.7 64.4 88.8 57.1 69.3 39.6 89.3 35.4 

4.2 0.7 62.4 91.3 57.0 69.5 39.6 90.7 35.9 

4.4 0.7 61.5 90.9 55.9 71.1 39.8 87.6 34.8 

5.1 0.7 64.6 90.6 58.5 68.5 40.1 82.5 33.1 

5.1 0.7 65.9 93.1 61.3 65.6 40.2 89.3 35.9 

3.7 0.8 74.9 87.9 65.8 61.2 40.3 84.0 33.8 

5.0 0.8 64.2 89.4 57.4 70.5 40.5 84.6 34.2 

4.7 0.7 68.4 91.5 62.5 64.7 40.5 88.2 35.7 

4.6 0.7 66.3 90.8 60.2 67.4 40.6 84.9 34.5 

4.6 0.7 65.0 91.4 59.4 69.1 41.0 76.9 31.6 

Series 2, No. 138 [ Page 41 
ages of data collection: National Immunization Survey, 2002—Con. 

Access Access rate × 

Percentage rate × Percentage completion 

Percentage of of children completion of children rate × adequate 

children Household Access Access with rate × with provider data 

9–35 months old eligibility Eligibility Ratio of rate Interview rate × adequate adequate complete rate × complete 

in telephone rate benchmark HER to EB (column 1 × completion completion provider provider provider provider data 

households (HER) (EB) (HER/EB) column 4) rate rate data data rate response rate 

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) 

90.5 3.4 4.5 0.7 67.4 89.5 60.3 69.6 42.0 87.6 36.8 94.7 3.0 4.0 0.8 70.7 89.2 63.0 67.0 42.2 84.0 35.5 94.6 3.3 4.6 0.7 68.7 87.3 59.9 70.5 42.3 86.2 36.4 

93.9 3.4 4.6 0.8 70.3 89.5 62.9 67.3 42.3 79.9 33.8 

91.9 5.6 7.6 0.7 67.2 92.2 61.9 68.8 42.6 83.8 35.7 92.8 3.3 4.4 0.8 69.8 92.6 64.6 66.3 42.9 87.1 37.3 90.2 3.3 4.5 0.7 66.2 90.4 59.8 72.4 43.3 85.8 37.2 95.6 5.9 8.1 0.7 69.9 90.6 63.3 70.3 44.5 79.6 35.4 86.7 3.3 4.6 0.7 62.8 92.1 57.9 77.1 44.6 82.9 37.0 95.1 3.7 4.8 0.8 73.4 90.6 66.5 67.0 44.6 82.1 36.6 

90.7 3.1 4.2 0.7 66.8 88.4 59.1 75.4 44.6 86.1 38.4 88.2 3.4 4.5 0.8 66.3 90.6 60.1 74.7 44.9 86.4 38.8 93.4 2.9 4.1 0.7 66.5 94.3 62.7 71.7 45.0 88.4 39.8 

94.4 3.7 4.7 0.8 73.5 90.2 66.3 68.2 45.2 92.4 41.8 

91.6 3.6 4.7 0.8 70.8 90.0 63.7 71.3 45.4 85.6 38.9 

95.6 3.2 4.5 0.7 67.7 92.0 62.3 72.8 45.4 87.1 39.5 93.4 3.7 4.6 0.8 75.3 88.1 66.3 69.4 46.0 84.4 38.8 93.5 3.4 4.5 0.8 71.9 89.8 64.6 71.8 46.4 88.1 40.8 

96.4 2.9 3.9 0.7 71.4 91.8 65.6 72.0 47.2 82.7 39.0 95.1 2.7 3.7 0.7 70.7 90.9 64.2 74.1 47.6 86.8 41.3 96.1 3.0 4.2 0.7 68.8 93.0 64.0 75.3 48.2 88.8 42.8 95.1 3.4 4.5 0.8 71.4 93.7 66.9 72.1 48.3 87.9 42.4 95.0 4.6 5.8 0.8 75.3 94.8 71.4 68.2 48.7 82.1 40.0 94.6 3.8 4.8 0.8 74.7 92.1 68.8 70.9 48.8 91.4 44.6 

94.8 3.3 4.4 0.8 71.8 91.9 65.9 74.7 49.3 88.8 43.7 95.0 3.4 4.4 0.8 74.4 92.0 68.5 72.4 49.6 90.5 44.9 93.2 3.9 4.8 0.8 77.1 94.1 72.6 71.4 51.8 82.4 42.7 95.6 3.2 4.2 0.8 72.3 94.0 68.0 76.2 51.8 84.2 43.6 95.3 4.3 5.8 0.7 70.8 93.5 66.2 79.2 52.4 81.6 42.8 92.8 3.7 4.4 0.8 77.5 94.6 73.3 71.5 52.4 87.1 45.6 93.0 3.9 4.6 0.9 79.1 91.1 72.1 73.6 53.1 87.9 46.6 95.8 3.7 4.6 0.8 77.1 91.1 70.3 77.8 54.7 90.0 49.2 95.1 2.9 3.6 0.8 76.6 92.6 70.9 79.8 56.6 89.4 50.6 

Page 42 [ Series 2, No. 138 

ascending order of their value in column 9. 
Series 2, No. 138 [ Page 43 

Table 6. Child, maternal, and household characteristics of children with a completed random-digit-dialed interview and children who had 

adequate provider data: National Immunization Survey, 2002 

Children with completed RDD interview1 Children with adequate provider data 

Unweighted Weighted Unweighted Weighted 

Characteristic sample size percent2 sample size percent3 

Total sample size or percent ...........................

Child 

Race/ethnicity: 

Hispanic ...................................... 

Non-Hispanic white ................................ 

Non-Hispanic black ................................ 

Non-Hispanic American Indian ......................... 

Non-Hispanic Asian ............................... 

Sex: 

Male ......................................... 

Female ....................................... 

Age: 

19–24 months ................................... 

25–29 months ................................... 

30–35 months ................................... 

Foreign born: 

Yes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 

No . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 

Mother 

Marital status (or deceased):

Widowed/divorced/separated/deceased ...................

Never married ...................................

Married .......................................

Educational attainment:

Less than 12 years ................................

12 years ......................................

More than 12, not college graduate ......................

College graduate .................................

Preferred language:

English .......................................

Spanish .......................................

Other ........................................

Age:

19 years or under ................................

20–29 years ....................................

30 years or over .................................

Household 

Annual income and poverty status:

Above $75,000/year ...............................

Above poverty, $75,000/year or less .....................

Below poverty ...................................

Unknown ......................................

Number of children under 18 years of age living in the household:

1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2–3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4 or more .....................................

Moved from another State since child’s birth:

Moved .......................................

Did not move ...................................

Unknown ......................................

MSA:4

MSA, central city .................................

MSA, not in central city .............................

Non-MSA ......................................

31,693 

6,517 

18,138 

5,094 

455 

1,489 

16,299 

15,394 

11,408 

9,421 

10,864 

429 

31,264 

2,449 

6,329 

22,915 

4,069 

9,115 

5,920 

12,589 

28,010 

3,105 

578 

862 

13,406 

17,425 

6,025 

15,981 

5,696 

3,991 

9,102 

18,626 

3,965 

2,868 

28,360 

465 

14,255 

11,255 

6,183 

100.0 

24.4 

55.6 

14.5 

1.2 

4.4 

51.5 

48.5 

35.8 

29.6 

34.6 

1.4 

98.6 

8.2 

21 

70.8 

17.3 

35.4 

15.3 

32 

85.4 

12.7 

1.9 

3.1 

45.1 

51.7 

16.9 

48.9 

21.1 

13.2 

27.4 

59.5 

13.1 

8.6 

90 

1.4 

34.7 

46.5 

18.8 

21,410 

4,194 

12,944 

2,992 

324 

956 

11,024 

10,386 

7,766 

6,340 

7,304 

198 

21,212 

1,581 

4,070 

15,759 

2,626 

6,103 

3,986 

8,695 

19,080 

1,995 

335 

548 

8,833 

12,029 

4,372 

11,218 

3,864 

1,956 

5,991 

12,791 

2,628 

1,733 

19,607 

70 

9,259 

7,641 

4,510 

100.0 

24.4 

55.7 

14.5 

1.2 

4.3 

51.5 

48.5 

36.2 

29.1 

34.6 

1.1 

98.9 

7.7 

21.7 

70.6 

17.4 

35.3 

15.6 

31.7 

85.3 

12.9 

1.8 

3.3 

44.8 

51.8 

17.2 

49.4 

21.2 

12.2 

27.2 

59.7 

13.1 

8.5 

91.2 

0.4 

35.1 

46.6 

18.3 

1RDD is random-digit-dialed.

2Figures in this column are based on the RDD-phase sampling weights.

3Figures in this column are based on the 2002 weighting methodology, which accounts for partial nonresponse, children who have received no vaccinations, and the 2002 revision of the nontelephone

adjustment.

4MSA is metropolitan statistical area.
Page 44 [ Series 2, No. 138 

Table 7. Estimated percentage of children 2 years of age residing in telephone households by immunization action plan area: United States, 

1996–97 and 2000 

Percent with a telephone Percent with a telephone 

IAP area1 1996–97 2000 IAP area1 1996–97 2000 

Mississippi ..................... 81.7 85.3 IN–Marion County ................. 89.9 93.4 

MI–Detroit ...................... 90.7 86.3 Montana ....................... 89.0 93.4 

Arkansas ...................... 75.9 86.7 FL–Miami–Dade County ............. 89.4 93.5 

AZ–Rest of State ................. 90.1 87.4 NY–New York City ................ 89.6 93.5 

West Virginia .................... 87.9 87.5 OH–Rest of State ................. 92.9 93.5 

Kentucky ...................... 86.7 88.2 AZ–Maricopa County ............... 86.6 93.8 

AL–Rest of State ................. 87.7 88.3 MI–Rest of State ................. 91.4 93.9 

IL–City of Chicago ................ 87.2 88.3 OH–Cuyahoga County .............. 84.9 94.1 

Oklahoma ...................... 82.1 88.4 Nevada ....................... 94.6 94.2 

NJ–City of Newark ................ 92.1 88.5 Rhode Island .................... 93.0 94.2 

MD–Baltimore City ................ 93.3 89.2 CA–Los Angeles County ............. 89.2 94.3 

LA–Rest of State ................. 82.8 89.3 MD–Rest of State ................. 93.3 94.4 

TX–City of Houston ................ 84.9 90.1 NJ–Rest of State ................. 92.1 94.4 

South Carolina ................... 80.9 90.2 OH–Franklin County ............... 92.9 94.4 

WI–Milwaukee County .............. 93.9 90.5 New Mexico .................... 85.7 94.5 

District of Columbia ................ 81.0 90.6 Connecticut ..................... 96.4 94.6 

GA–Rest of State ................. 79.7 90.6 Nebraska ...................... 95.1 94.6 

TX–Rest of State ................. 84.3 90.6 Hawaii ........................ 94.3 94.7 

TN–Rest of State ................. 86.4 90.7 PA–Rest of State ................. 97.1 94.7 

North Carolina ................... 87.8 91.0 WI–Rest of State ................. 93.9 94.8 

TX–Dallas County ................. 92.1 91.4 CA–Rest of State ................. 92.8 94.9 

FL–Duval County ................. 89.4 91.5 MA–City of Boston ................ 94.5 94.9 

LA–Orleans Parish ................ 82.8 91.5 Alaska ........................ 93.9 95.0 

IN–Rest of State .................. 89.9 91.6 Iowa ......................... 94.1 95.0 

FL–Rest of State ................. 89.4 91.8 NY–Rest of State ................. 95.2 95.0 

TN–Shelby County ................ 86.4 91.9 Colorado ...................... 95.8 95.1 

TX–El Paso County ................ 84.3 91.9 Maine ........................ 95.9 95.1 

TX–Bexar County ................. 84.3 92.1 Oregon ....................... 94.3 95.1 

Delaware ...................... 93.0 92.3 Vermont ....................... 95.5 95.1 

PA–Philadelphia County ............. 94.7 92.6 WA–Rest of State ................. 95.6 95.2 

Virginia ....................... 93.0 92.6 Idaho ......................... 91.7 95.3 

Missouri ....................... 89.4 92.8 CA–San Diego County .............. 92.8 95.4 

Wyoming ...................... 89.6 92.8 MA–Rest of State ................. 92.8 95.6 

South Dakota ................... 84.9 93.0 New Hampshire .................. 92.1 95.6 

TN–Davidson County ............... 86.4 93.1 Utah ......................... 96.3 95.6 

AL–Jefferson County ............... 87.7 93.2 Minnesota ...................... 97.0 95.8 

Kansas ....................... 89.1 93.2 North Dakota .................... 96.7 96.1 

GA–Fulton/DeKalb Counties .......... 94.3 93.3 WA–King County ................. 95.6 96.4 

IL–Rest of State .................. 84.0 93.3 CA–Santa Clara County ............. 92.8 96.5 

1IAP is immunization action plan. 

NOTE: IAP areas are listed in order of the estimated percentage for 2000. The 2000 estimate for an IAP area equals the product of the estimate from the 2000 census and an adjustment factor for the

corresponding census region that aligns the 2000 census estimate for the region with the region’s estimate from the March 2000 Current Population Survey.

SOURCE: U.S. Census Bureau, Current Population Surveys, 1996–97 and March 2000; and Census 2000.
Series 2, No. 138 [ Page 45 

Table 8. Number of sample children by each combination of the three characteristics that define poststratification cells, with

poststratification cells produced by the collapsing procedure: Massachusetts—City of Boston, second, third, and fourth quarters of 1994

Education of mother 

12 years or less More than 12 years 

Age of child 

Race/ethnicity 19–25 months 26–35 months 19–25 months 26–35 months 

Hispanic .............................. 13 24 9 12

Non-Hispanic black ....................... 23 36 14 24

Non-Hispanic white or other .................. 23 30 39 52

Number of 

Poststratification cell children 

Hispanic ...................................... . ...................................... 58

Non-Hispanic black, education 12 years or less ..................................................... 59

Non-Hispanic black, education more than 12 years ................................................... 38

Non-Hispanic white or other, education 12 years or less ................................................ 53

Non-Hispanic white or other, education more than 12 years, age 19–25 months ................................. 39

Non-Hispanic white or other, education more than 12 years, age 26–35 months ................................. 52
Page 46 [ Series 2, No. 138 

Table 9. Prevalence of selected characteristics by the combination of household telephone status at the time of the survey and interruption 

in telephone service: Nine large States, 1997–99 

No phone No phone, Phone with Phone and 

State and characteristic with interruption no interruption interruption no interruption 

California 

No insurance ..................................... 37.60 38.65 31.72 18.27 

Self-reported fair/poor health ........................... 10.97 14.62 10.23 8.19 

Medicaid eligibility .................................. 38.24 35.91 31.21 11.24 

No health care–cost barrier1 ........................... 8.35 8.92 10.25 3.78 

Texas 

No insurance ..................................... 55.16 52.09 39.08 20.87 

Self-reported fair/poor health ........................... 12.73 13.87 9.89 8.58 

Medicaid eligibility .................................. 16.66 21.52 19.14 6.11 

No health care–cost barrier1 ........................... 8.17 10.42 10.82 4.19 

Florida 

No insurance ..................................... 51.90 51.68 27.61 18.13 

Self-reported fair/poor health ........................... 13.22 14.26 12.78 9.55 

Medicaid eligibility .................................. 22.38 16.39 20.68 5.92 

No health care–cost barrier1 ........................... 17.15 14.20 9.90 5.18 

Michigan 

No insurance ..................................... 39.35 22.39 25.81 8.72 

Self-reported fair/poor health ........................... 9.93 14.46 14.36 7.22 

Medicaid eligibility .................................. 28.65 40.95 32.69 7.80 

No health care–cost barrier1 ........................... 9.84 8.83 10.26 3.49 

Illinois 

No insurance ..................................... 32.30 36.56 24.93 9.99 

Self-reported fair/poor health ........................... 7.77 14.74 7.50 7.04 

Medicaid eligibility .................................. 45.60 33.94 22.67 5.21 

No health care–cost barrier1 ........................... 11.14 10.04 6.54 2.59 

New Jersey 

No insurance ..................................... 23.04 35.83 19.91 12.60 

Self-reported fair/poor health ........................... 2.87 13.17 9.83 7.20 

Medicaid eligibility .................................. 52.24 32.81 17.14 4.81 

No health care–cost barrier1 ........................... 4.63 11.85 7.94 2.95 

New York 

No insurance ..................................... 24.02 29.08 24.76 13.30 

Self-reported fair/poor health ........................... 10.33 22.00 12.63 8.32 

Medicaid eligibility .................................. 50.00 48.78 29.51 10.51 

No health care–cost barrier1 ........................... 4.76 8.63 10.24 3.38 

Ohio 

No insurance ..................................... 37.37 28.21 19.43 9.83 

Self-reported fair/poor health ........................... 10.51 18.33 14.17 8.88 

Medicaid eligibility .................................. 19.32 25.89 21.33 5.39 

No health care–cost barrier1 ........................... 10.13 9.89 18.45 3.90 

Pennsylvania 

No insurance ..................................... 22.27 31.35 19.18 7.90 

Self-reported fair/poor health ........................... 15.27 16.76 6.69 8.43 

Medicaid eligibility .................................. 51.29 26.54 18.12 6.15 

No health care–cost barrier1 ........................... 8.97 16.71 5.91 3.04 

1The respondent reported not receiving health care because of cost barriers.

NOTE: The National Health Interview Survey is currently not designed to yield State-level estimates. These nine States had a sufficiently large sample to yield reliable estimates for the four categories

defining the columns of the table.

SOURCE: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey, 1997–99.
Series 2, No. 138 [ Page 47 

Table 10. Calculations for applying the interruption-based adjustment: Georgia—Rest of State immunization action plan area, 2001 

Step 

number Description Calculation 

1 Population number of children N++ = 148,344 

2 Estimated proportion of children (2 years of age) in telephone households 1

0.79687 

3 Number of children in telephone households NT+ = 148,344 × 0.79687 = 118,211 

4 Number of children in nontelephone households NT+ = N++ – NT+ = 148,344 – 118,211 = 30,133 

Weighted proportion of children in telephone households with an interruption in 

5 telephone service 20.07611 

^ 6 Estimated number of children from telephone households with interruptions NTI = NT+ × 0.07611 = 118,211 × 0.07611 = 8,998 

^ 7 Control total for children from telephone households without interruptions NT+ – NTI = 118,211 – 8,998 = 109,213 

^ 8 Control total for children from telephone households with interruptions NT+ + NTI = 30,133 + 8,998 = 39,131 

9 Adjustment factor for children from telephone households without interruptions 3109,213/95,799 = 1.140 

10 Adjustment factor for children from telephone households with interruptions 4

39,131/7,892 = 4.958 

11 Ratio of the adjustment factors 54.958/1.140 = 4.349 

Truncate the adjustment factor for children from telephone households with 

12 interruptions 1.140 × 3.0 = 3.420 

For each child from a telephone household without an interruption, multiply the 

13 nonresponse-adjusted base sampling weight by 1.140 

For each child from a telephone household with an interruption, multiply the 

14 nonresponse-adjusted base sampling weight by 3.420 

Poststratify the sample of children to the population control totals for the 

15 poststratification cells 

1This figure is from the 1996–97 Current Population Survey. See table 7 of this report.

2This figure is from the National Immunization Survey sample, with the nonresponse-adjusted base sampling weight.

395,799 is the sum of the nonresponse-adjusted base sampling weights for such children.

47,892 is the sum of the nonresponse-adjusted base sampling weights for such children.

5The ratio of the adjustment factors exceeds 3.0.
s revised to account for children with no vaccinations and incorporating new nontelephone adjustment by State: National Immunization 

DTP41 DTP32 POL3 MMR4 MCV5 HIB6 HEP7 VRC8 4:3:19 3:3:110 4:3:1:311 4:3:1:3:312 

n1+ n0 % ∆ % ∆ % ∆ % ∆ % ∆ % ∆ % ∆ % ∆ % ∆ % ∆ % ∆ % ∆ 

23,531 111 81.8 –0.3 93.9 –0.4 89.0 –0.4 91.1 –0.3 91.3 –0.3 92.8 –0.2 88.8 –0.1 76.5 0.2 78.2 –0.4 84.0 –0.4 76.9 –0.3 73.4 –0.3 

591 1 86.8 0.0 97.4 –0.9 92.3 –0.4 94.4 0.4 94.7 0.4 97.2 0.0 92.0 0.8 89.3 1.2 83.9 –0.6 89.3 –0.6 82.4 –0.3 78.8 –0.3

289 3 76.6 –0.4 89.4 –0.4 84.4 –0.5 87.8 0.0 88.1 –0.1 87.7 –0.6 84.4 0.0 61.1 0.0 74.2 –0.3 80.7 –0.3 73.9 –0.2 70.8 –0.4

590 2 78.9 1.0 93.6 0.7 85.9 0.0 88.7 0.0 88.8 0.0 91.2 0.0 85.5 0.5 74.9 0.4 74.1 0.3 81.0 0.0 73.2 0.3 68.0 –0.1

391 1 75.2 –2.0 94.8 0.6 88.4 –0.5 89.1 –1.2 89.2 –1.2 92.5 –0.7 86.1 –0.5 82.5 –0.6 72.5 –1.6 83.0 –0.8 72.5 –1.6 68.1 –1.0

1,261 5 79.1 –0.7 93.4 –0.3 88.0 –0.8 90.8 –0.5 91.0 –0.6 92.1 –0.2 89.2 0.4 82.1 –0.9 76.1 –0.4 83.1 –0.9 74.6 –0.3 72.3 –0.3

368 4 80.1 –1.6 94.4 –1.2 89.1 –1.2 91.3 –0.8 91.5 –0.8 90.7 –1.6 86.8 –0.8 78.6 –0.4 75.5 –1.7 83.9 –0.9 73.6 –1.8 69.9 –1.6

285 1 90.1 0.2 94.8 –0.2 93.9 –0.3 93.8 –0.1 93.8 –0.1 94.4 –0.1 89.6 0.6 83.9 –0.4 86.0 0.1 87.7 0.0 84.3 0.2 79.1 0.7

281 0 87.7 0.8 93.6 –0.2 91.6 1.0 93.4 –0.2 93.6 –0.3 93.8 0.6 90.7 0.8 81.0 0.4 81.8 0.8 84.2 0.2 79.5 0.9 75.8 0.9

311 1 79.8 –0.6 91.7 0.1 88.4 –0.2 92.5 0.6 92.9 0.7 91.4 –0.2 84.7 –2.2 85.5 –1.1 75.6 0.1 84.2 0.5 74.1 –0.1 67.5 –1.4

811 1 83.8 –0.4 94.1 0.1 90.5 0.6 91.2 –0.2 91.3 –0.2 92.5 –0.4 87.7 –1.0 73.2 1.2 79.3 –0.1 83.1 –0.1 76.8 –0.1 72.1 –0.9

598 0 84.5 0.3 94.7 0.0 93.1 0.0 90.9 0.8 91.3 0.7 93.6 0.3 92.7 0.3 88.3 1.2 81.8 0.5 87.5 0.9 80.7 0.7 79.3 0.8

278 1 77.9 0.7 91.2 0.8 84.8 1.2 90.7 0.1 91.0 0.0 90.7 0.8 87.7 1.1 81.1 0.4 74.6 1.2 79.6 1.4 74.1 1.3 72.0 1.2

327 2 75.2 –1.2 91.3 –0.5 84.3 –0.8 87.2 –1.4 87.2 –1.4 90.4 –1.1 86.1 –0.3 56.3 0.5 73.9 –1.1 80.4 –1.1 73.3 –0.8 69.3 –0.9

602 3 81.8 0.6 93.0 0.5 86.5 1.0 89.3 0.3 89.7 0.1 92.6 0.7 88.8 0.7 58.2 1.2 76.7 0.3 81.8 0.7 76.1 0.5 73.3 0.6

559 3 78.9 0.5 92.8 0.1 89.6 0.2 91.3 0.2 91.3 0.2 93.3 0.6 89.7 0.9 61.0 2.1 75.6 0.1 82.1 0.0 74.0 0.4 71.7 0.6

292 2 85.1 1.1 94.0 0.0 89.7 0.6 89.4 0.2 89.4 0.2 93.5 0.2 92.5 0.4 63.5 1.1 81.2 1.1 83.8 0.8 80.3 0.9 79.6 1.0

269 2 82.6 0.1 93.9 1.8 91.0 2.5 91.6 1.2 91.6 1.2 94.1 1.6 90.3 1.5 65.8 1.7 78.0 1.3 84.7 2.8 77.2 1.5 74.4 1.6

305 1 83.0 1.4 95.5 0.5 92.5 0.3 91.7 0.1 92.3 –0.1 94.0 0.7 91.6 1.3 79.5 2.0 80.9 0.7 87.1 0.2 79.5 1.0 77.2 1.3

572 5 73.3 –0.8 88.5 –0.7 80.1 –1.3 83.4 –1.3 83.4 –1.3 89.5 –0.6 85.7 0.1 70.9 –2.1 69.7 –0.2 73.6 –0.6 69.0 0.1 65.5 1.4

310 5 89.5 –0.9 96.7 –1.1 92.0 –1.0 93.2 –1.0 93.5 –1.0 94.0 –1.1 86.3 –1.3 62.2 0.1 82.4 –0.9 87.6 –0.9 81.2 –1.0 74.0 –1.1

632 3 82.6 –0.7 93.4 –0.2 89.8 –1.1 92.9 0.0 92.9 0.0 93.6 0.0 89.7 –0.1 88.0 0.2 79.1 –0.6 84.9 –1.0 77.3 –0.6 72.9 –0.5

599 1 85.6 –0.1 95.6 –0.4 92.7 –0.2 91.8 –1.0 91.8 –1.0 97.9 0.0 92.9 0.4 83.2 0.4 81.3 –0.6 84.9 –0.9 80.2 –0.4 76.5 –0.1

601 3 76.3 –1.4 93.2 –1.8 87.1 –1.2 87.6 –1.0 87.9 –1.0 91.8 –1.3 86.9 0.5 77.6 1.0 73.4 –1.3 82.7 –0.4 72.7 –1.2 69.7 –0.3

306 2 86.2 –0.1 97.0 –0.3 91.3 –0.3 91.2 0.4 91.2 0.4 93.5 0.1 92.2 –0.3 74.5 0.8 81.1 –0.2 85.9 –0.2 79.1 0.1 75.9 –0.4

286 0 89.0 1.5 97.1 0.7 93.6 0.8 93.5 0.2 93.5 0.2 94.0 0.7 92.9 1.6 63.1 1.6 86.1 1.6 90.3 1.0 84.8 0.9 81.7 1.5

267 2 83.1 –0.7 95.3 –0.6 87.8 –1.9 89.8 –0.2 90.2 –0.3 92.5 –1.2 89.5 –1.6 69.4 0.7 78.1 –0.9 83.4 –1.2 76.9 –0.9 74.9 –0.6

290 5 83.7 –1.8 96.1 –1.0 88.3 –1.3 94.1 –0.6 94.1 –0.6 94.5 –0.6 90.2 –1.1 66.8 –0.4 81.6 –1.4 86.3 –0.9 80.5 –1.2 76.7 –1.2

301 0 84.1 –1.3 93.8 –0.4 88.5 –0.4 90.9 0.0 90.9 0.0 92.3 0.3 90.7 –0.5 68.4 –0.7 80.2 –1.3 82.7 –1.2 79.0 –1.4 77.7 –1.2

297 1 76.2 0.4 89.6 –0.6 86.3 0.3 87.1 1.1 87.4 1.1 88.8 –0.8 84.8 –0.7 68.3 1.3 74.7 0.8 80.7 0.7 72.4 0.2 68.2 0.1

318 1 87.0 –1.8 98.1 –0.1 93.1 –1.3 93.0 –1.3 93.2 –1.4 97.2 –0.2 90.5 0.5 73.3 0.0 83.1 –1.8 89.0 –1.4 82.1 –1.8 76.4 –1.2

636 4 78.9 –2.4 90.2 –2.2 85.3 –3.1 90.9 –0.2 91.8 –0.3 89.6 –2.8 82.0 –3.8 74.4 –1.1 75.0 –2.9 80.9 –2.5 72.6 –3.6 69.7 –3.4

338 0 76.0 –0.1 92.0 –0.5 84.3 0.0 87.1 –0.6 87.1 –0.6 90.3 0.0 78.9 –0.4 71.9 –0.4 72.7 0.0 79.3 –0.3 71.0 0.0 63.1 –0.1

589 2 86.2 –1.2 95.3 0.1 88.3 –1.0 92.2 –0.3 92.6 –0.3 94.0 0.6 89.4 –0.3 78.4 –0.6 80.1 –1.8 83.3 –1.4 79.0 –1.5 75.6 –1.5

301 2 87.9 1.0 97.7 –0.6 93.4 0.3 96.0 –0.4 96.3 –0.4 94.0 0.0 91.7 –0.4 83.6 0.5 86.8 1.1 90.5 0.4 85.9 1.2 81.3 0.9

318 2 85.7 –0.3 93.6 –0.5 92.2 –0.4 92.3 –0.2 92.3 –0.2 93.5 –1.0 89.2 –0.5 68.4 –0.8 83.3 –0.2 89.2 –0.2 82.1 –0.4 78.1 –0.6

920 3 78.0 –0.5 92.8 –0.6 88.8 –1.2 91.6 –0.2 91.6 –0.3 92.5 –0.7 89.6 –0.7 70.8 –1.3 75.9 –0.4 82.8 –0.5 74.3 –0.4 71.1 –0.1

315 2 79.2 –0.9 91.9 –1.7 84.9 –1.8 93.0 –0.8 93.0 –0.8 89.9 –1.0 84.0 –0.6 83.0 0.5 76.7 –0.4 82.5 –1.3 76.2 0.0 70.3 0.3

286 2 78.3 0.1 94.5 –0.3 87.2 –1.3 88.2 –1.2 88.5 –1.2 90.7 –0.7 87.8 –1.2 73.3 –0.9 74.8 –0.5 81.7 –1.0 72.7 –0.3 68.2 –0.3

564 4 87.0 –0.1 96.8 –0.4 91.7 –0.4 95.3 –0.2 95.5 –0.3 93.7 –0.4 91.3 –0.2 80.7 0.6 84.4 –0.2 89.4 –0.2 81.9 –0.1 78.7 –0.1

364 1 89.1 –0.8 95.9 –1.2 94.9 0.0 95.3 0.5 95.8 0.4 96.5 –0.3 94.9 –0.9 89.0 –0.9 84.4 –0.4 88.6 –0.5 83.3 –0.4 80.9 –0.8

296 0 82.4 –0.3 95.6 –0.4 93.6 0.9 95.4 0.7 95.7 0.7 96.0 0.2 93.1 0.8 79.2 –1.0 80.9 –0.3 90.2 0.6 80.5 –0.3 78.7 0.0

265 5 81.8 –1.4 93.6 –1.8 89.9 –1.3 93.0 –0.7 93.0 –0.7 93.2 –1.7 90.0 –0.5 53.7 0.9 79.5 –1.0 86.8 –0.7 77.9 –1.2 75.9 –0.6

916 1 85.5 –0.8 95.8 0.7 93.8 0.3 94.2 0.0 94.2 0.0 96.5 0.5 91.9 0.4 80.2 0.1 84.0 –0.6 89.0 0.3 83.2 –0.7 79.3 –0.4

1,594 2 78.8 0.2 93.2 –0.1 87.9 0.3 90.1 –0.3 90.1 –0.3 91.4 0.3 86.8 –0.1 83.3 –0.2 75.6 0.7 83.1 0.0 74.4 0.7 69.9 0.2

302 3 80.0 0.6 91.5 –0.5 88.1 –0.3 89.2 0.1 89.2 0.1 91.0 –0.9 83.0 0.3 69.3 1.2 75.7 0.6 82.9 0.0 74.2 0.1 66.4 0.3

Page 48 [ Series 2, No. 138 
s revised to account for children with no vaccinations and incorporating new nontelephone adjustment by State: National Immunization 

DTP41 DTP32 POL3 MMR4 MCV5 HIB6 HEP7 VRC8 4:3:19 3:3:110 4:3:1:311 4:3:1:3:312 

n1+ n0 % ∆ % ∆ % ∆ % ∆ % ∆ % ∆ % ∆ % ∆ % ∆ % ∆ % ∆ % ∆ 

331 3 91.3 –0.4 97.1 –0.5 94.7 –0.5 95.1 –0.5 95.1 –0.5 96.5 –0.5 86.1 –1.2 61.2 –0.7 88.9 –0.3 92.3 –0.5 87.8 –0.2 79.4 –0.9 

243 0 82.9 –0.4 94.8 0.3 88.7 0.1 91.3 0.3 91.3 0.3 95.7 0.6 89.5 0.0 82.0 –1.1 77.9 –0.5 83.0 0.0 77.4 –0.6 73.6 –1.3 

592 8 78.3 –1.6 89.2 –1.6 87.2 –1.3 87.6 –1.7 87.7 –1.8 89.3 –1.3 85.1 –0.9 57.0 0.0 75.1 –1.6 80.0 –1.9 73.9 –1.6 69.5 –1.7 

287 1 87.9 –0.3 96.5 –0.4 91.1 –0.1 93.4 –0.4 93.4 –0.4 97.6 –0.6 91.1 –0.8 75.2 2.2 82.7 0.6 86.9 0.6 81.2 0.2 77.7 –0.4 

601 4 86.6 –0.6 94.8 –0.3 90.5 –0.3 91.4 –0.9 91.6 –1.1 93.1 –0.1 91.1 –0.1 67.6 0.4 83.1 –0.7 86.5 –0.9 81.9 –0.6 79.3 –0.2 

286 1 81.5 –2.2 92.4 –2.3 87.9 –1.3 88.8 –2.8 89.0 –2.8 93.9 –1.4 85.6 –1.2 57.5 –3.4 78.9 –2.0 83.1 –2.6 78.6 –2.0 72.1 –2.2 

of diphtheria and tetanus toxoids and pertussis vaccine).of diphtheria and tetanus toxoids and pertussis vaccine).

of polio vaccine).

of measles, mumps, and rubella vaccine, not including any measles-only shots).

of measles-containing vaccine).

Haemophilus influenzae type b vaccine).

of hepatitis B vaccine).

of varicella vaccine) at 12 or more months of age.

iphtheria and tetanus toxoids and pertussis vaccine, 3 or more doses of polio vaccine, and 1 or more doses of measles-containing vaccine).

diphtheria and tetanus toxoids and pertussis vaccine, 3 or more doses of polio vaccine, and 1 or more doses of measles-containing vaccine).

f diphtheria and tetanus toxoids and pertussis vaccine, 3 or more doses of polio vaccine, 1 or more doses of measles-containing vaccine, and 3 or more doses of Haemophilus influenzae type b vaccine).

of diphtheria and tetanus toxoids and pertussis vaccine, 3 or more doses of polio vaccine, 1 or more doses of measles-containing vaccine, 3 or more doses of Haemophilus influenzae type b vaccine,

with no vaccinations, nNIT denotes the number of children living in a household that did not experience an interruption in telephone service, nIT denotes the number of children living in a household that did

+ denotes the number of children with one or more vaccinations, n0 denotes the number of children with no vaccinations, and ∆ denotes the difference between the revised coverage rate listed in the table

ildren with zero vaccinations or incorporate the new nontelephone adjustment.

Series 2, No. 138 [ Page 49 
Page 50 [ Series 2, No. 138 

Table 12. Differences in estimates of 4:3:1:3 vaccination coverage produced by using the new nontelephone adjustment and accounting for 

children with no vaccinations by State: National Immunization Survey, 2001 

Change in estimate caused by— 

Accounting for Using the new 

Accounting children with no nontelephone 

Estimate Using only only for vaccinations adjustment and 

based on Standard the new children (after making accounting for 

1998–2001 error of nontelephone with no new nontelephone children with no 

State methodology1 estimate adjustment2 vaccinations3 adjustment)4 vaccinations5 

United States total ................ 77.2 0.4 –0.3 –0.1 0.0 –0.3 

Alabama ....................... 82.7 2.0 –0.1 –0.1 –0.2 –0.3 

Alaska ........................ 74.1 2.8 –0.3 0.0 0.1 –0.2 

Arizona ....................... 72.9 2.1 1.1 –0.5 –0.8 0.3 

Arkansas ...................... 74.1 2.4 –1.4 0.0 –0.2 –1.6 

California ...................... 74.9 1.8 –0.5 0.3 0.2 –0.3 

Colorado ...................... 75.4 2.4 –1 –0.9 –0.8 –1.8 

Connecticut ..................... 84.1 2.5 –0.1 0.1 0.3 0.2 

Delaware ...................... 78.6 2.6 0.6 0.1 0.3 0.9 

District of Columbia ................ 74.2 2.9 0.2 –0.3 –0.3 –0.1 

Florida ........................ 76.9 2.2 –0.3 0.1 0.2 –0.1 

Georgia ....................... 80.0 2.2 0.4 0.3 0.3 0.7 

Hawaii ........................ 72.8 3.4 0.7 1.3 0.6 1.3 

Idaho ......................... 74.1 2.7 –1.2 0.2 0.4 –0.8 

Illinois ........................ 75.6 2.1 0.3 0.4 0.2 0.5 

Indiana ....................... 73.6 2.4 0.2 0.0 0.2 0.4 

Iowa ......................... 79.4 2.6 1.2 –0.1 –0.3 0.9 

Kansas ....................... 75.7 3.5 –0.4 1.4 1.9 1.5 

Kentucky ...................... 78.5 2.5 1.0 –0.3 0.0 1.0 

Louisiana ...................... 68.9 2.8 0.8 –0.5 –0.7 0.1 

Maine ........................ 82.2 2.3 –0.1 –0.9 –0.9 –1 

Maryland ...................... 77.9 2.1 –0.4 –0.3 –0.2 –0.6 

Massachusetts ................... 80.6 2.2 –1 0.4 0.6 –0.4 

Michigan ...................... 73.9 2.5 –1.3 0.1 0.1 –1.2 

Minnesota ...................... 79.0 2.6 0.0 0.1 0.1 0.1 

Mississippi ..................... 83.9 2.5 0.7 0.6 0.2 0.9 

Missouri ....................... 77.8 2.7 –0.7 –0.2 –0.2 –0.9 

Montana ....................... 81.7 2.4 –0.2 –1.1 –1 –1.2 

Nebraska ...................... 80.4 2.4 –0.9 –0.3 –0.5 –1.4 

Nevada ....................... 72.2 2.9 0.0 0.5 0.2 0.2 

New Hampshire .................. 83.9 2.2 –1 –1 –0.8 –1.8 

New Jersey ..................... 76.2 2.7 –2.9 –0.8 –0.7 –3.6 

New Mexico .................... 71.0 2.6 0.3 –0.1 –0.3 0.0 

New York . . . . . . . . . . . . . . . . . . . . . . 80.5 1.8 –1.2 –0.3 –0.3 –1.5 

North Carolina ................... 84.7 2.4 2.2 –0.2 –1 1.2 

North Dakota .................... 82.5 2.3 0.1 –0.4 –0.5 –0.4 

Ohio ......................... 74.7 2.1 –0.4 –0.1 0.0 –0.4 

Oklahoma ...................... 76.2 2.8 –0.1 0.0 0.1 0.0 

Oregon ....................... 73.0 3.0 –0.2 0.1 –0.1 –0.3 

Pennsylvania .................... 82.0 2.1 0.4 –0.5 –0.5 –0.1 

Rhode Island .................... 83.7 2.1 –0.2 0.0 –0.2 –0.4 

South Carolina ................... 80.8 2.6 –0.1 0.1 –0.2 –0.3 

South Dakota ................... 79.1 2.8 –1 –0.2 –0.2 –1.2 

Tennessee ..................... 83.9 1.6 –0.7 0.1 0.0 –0.7 

Texas ........................ 73.7 1.9 0.5 –0.2 0.2 0.7 

Utah ......................... 74.1 2.8 0.1 –0.4 0.0 0.1 

Vermont ....................... 88.0 1.9 0.2 –0.6 –0.4 –0.2 

See footnotes at end of table. 
Series 2, No. 138 [ Page 51 

Table 12. Differences in estimates of 4:3:1:3 vaccination coverage produced by using the new nontelephone adjustment and accounting for 

children with no vaccinations by State: National Immunization Survey, 2001—Con. 

Change in estimate caused by— 

Accounting for Using the new 

Accounting children with no nontelephone 

Estimate Using only only for vaccinations adjustment and 

based on Standard the new children (after making accounting for 

1998–2001 error of nontelephone with no new nontelephone children with no 

State methodology1 estimate adjustment2 vaccinations3 adjustment)4 vaccinations5 

Virginia ....................... 78.0 3.1 –0.4 –0.5 –0.2 –0.6 

Washington ..................... 75.5 2.2 –1.1 –0.7 –0.5 –1.6 

West Virginia .................... 81.0 2.6 0.3 –0.2 –0.1 0.2 

Wisconsin ...................... 82.5 1.8 –0.1 –0.5 –0.5 –0.6 

Wyoming ...................... 80.6 2.6 –1.3 –0.6 –0.7 –2 

1The 4:3:1:3 estimate of vaccination coverage based on modified poststratification and not accounting for children with no vaccinations. 

2Difference between the 4:3:1:3 estimate of vaccination coverage that incorporates the new nontelephone adjustment but does not account for children with no vaccinations and the 4:3:1:3 estimate 

based on modified poststratification and not accounting for children with no vaccinations. 

3Difference between the 4:3:1:3 estimate of vaccination coverage that accounts for children with no vaccinations but does not incorporate the new nontelephone adjustment and the 4:3:1:3 estimate 

based on modified poststratification and not accounting for children with no vaccinations. 

4Difference between the 4:3:1:3 estimate of vaccination coverage that incorporates the new nontelephone adjustment and accounts for children with no vaccinations and the 4:3:1:3 estimate based on 

the new nontelephone adjustment but not accounting for children with no vaccinations. 

5Overall difference between the 4:3:1:3 estimate of vaccination coverage that incorporates the new nontelephone adjustment and accounts for children with no vaccinations and the 4:3:1:3 estimate 

based on modified poststratification and not accounting for children with no vaccinations. The overall difference equals the sum of columns 4 (using only the new nontelephone adjustment) and 6 

(accounting for children with no vaccinations, after making new nontelephone adjustment). 

NOTE: 4:3:1:3:3 refers to 4 or more doses of diphtheria and tetanus toxoids and pertussis vaccine (DTP), 3 or more doses of polio vaccine (polio), 1 or more doses of measles-containing vaccine 

(MCV), 3 or more doses of Haemophilus influenzae type b vaccine (Hib), and 3 or more doses of hepatitis B vaccine (Hep B). 

Table 13. Percentage of sampled children with adequate provider data who were incompletely ascertained by race/ethnicity: National 

Immunization Survey, 1995–2002 

Non-Hispanic 

Hispanic White Black American Indian Asian Other 

Survey year Percent CI1 Percent CI1 Percent CI1 Percent CI1 Percent CI1 Percent CI1 

1995 ............... 18.4 (±4.2) 15.0 (±1.1) 15.5 (±2.6) 12.9 (±7.4) 17.6 (±6.7) 19.5 (±15.6) 

1996 ............... 17.0 (±1.6) 13.9 (±1.3) 15.8 (±3.0) 11.7 (±4.3) 18.1 (±3.4) 5.6 (±6.9) 

1997 ............... 16.2 (±3.6) 13.5 (±1.4) 14.6 (±2.4) 15.1 (±6.4) 15.9 (±3.5) 16.0 (±6.1) 

1998 ............... 18.9 (±1.7) 15.9 (±1.3) 17.3 (±2.3) 19.7 (±12.3) 16.5 (±3.1) 13.6 (±6.0) 

1999 ............... 22.3 (±2.2) 17.7 (±1.6) 17.2 (±2.2) 25.8 (±12.1) 13.2 (±3.0) 14.9 (±9.2) 

2000 ............... 21.8 (±2.9) 16.2 (±1.9) 17.0 (±2.6) 18.6 (±5.1) 14.8 (±5.3) 15.2 (±24.0) 

2001 ............... 19.2 (±2.3) 13.2 (±1.1) 16.6 (±2.5) 10.6 (±5.3) 18.3 (±4.9) 51.4 (±53.0) 

2002 ............... 19.5 (±2.6) 14.1 (±1.1) 14.8 (±1.8) 21.0 (±8.2) 11.8 (±2.9) 12.1 (±25.2) 

1CI is half-width of 95-percent confidence interval. 
Page 52 [ Series 2, No. 138 

Table 14. State and national estimates of 4:3:1:3:3 vaccination coverage for the 2002 estimation methodology and the three alternative 

methodologies: National Immunization Survey, 2002 

Cases treated as missing 

2002 methodology 

(a) 

All underascertained 

cases 

(b) 

Underascertained 

cases who are not 

4:3:1:3:3 up to date 

(c) 

Underascertained cases 

who are not 4:3:1:3:3 up to date 

and incompletely ascertained 

shot card cases whose 

records do not agree with 

their providers’ records3 

(d) 

Difference in 

4:3:1:3:3 coverage 

State Percent CI1 CV2 Percent CI1 CV2 Percent CI1 CV2 Percent C11 CV2 b–a c–a d–a 

United States total ........... 74.8 (±1.0) 0.01 76.4 (±1.2) 0.01 79.1 (±1.0) 0.01 78.6 (±1.0) 0.01 1.6 4.3 3.8 

Alabama .................. 76.8 (±5.3) 0.04 79.6 (±5.4) 0.03 80.2 (±5.1) 0.03 79.9 (±5.1) 0.03 2.7 3.4 3.1 

Alaska ................... 75.3 (±5.7) 0.04 77.3 (±6.2) 0.04 80.3 (±5.3) 0.03 79.5 (±5.4) 0.03 2.0 5.0 4.2 

Arizona .................. 67.9 (±4.7) 0.04 69.1 (±6.1) 0.05 74.5 (±4.6) 0.03 73.3 (±4.6) 0.03 1.1 6.5 5.4 

Arkansas ................. 71.0 (±5.9) 0.04 71.6 (±6.7) 0.05 75.5 (±5.5) 0.04 74.5 (±5.7) 0.04 0.6 4.5 3.6 

California ................. 73.2 (±3.8) 0.03 75.4 (±4.2) 0.03 77.1 (±3.7) 0.02 76.8 (±3.7) 0.02 2.2 3.9 3.6 

Colorado ................. 62.7 (±6.5) 0.05 63.0 (±7.8) 0.06 67.3 (±6.5) 0.05 66.5 (±6.5) 0.05 0.3 4.6 3.7 

Connecticut ................ 81.9 (±5.2) 0.03 84.4 (±6.2) 0.04 85.8 (±5.0) 0.03 85.8 (±5.0) 0.03 2.5 3.9 3.9 

Delaware ................. 78.7 (±5.6) 0.04 83.7 (±5.4) 0.03 82.8 (±5.1) 0.03 82.2 (±5.1) 0.03 4.9 4.1 3.5 

District of Columbia ........... 69.7 (±7.5) 0.05 74.0 (±8.3) 0.06 75.0 (±7.4) 0.05 75.3 (±7.3) 0.05 4.3 5.3 5.6 

Florida ................... 74.5 (±4.8) 0.03 72.9 (±6.8) 0.05 78.8 (±4.5) 0.03 77.7 (±4.6) 0.03 –1.5 4.3 3.2 

Georgia .................. 80.4 (±4.2) 0.03 81.4 (±4.8) 0.03 82.9 (±4.1) 0.02 82.5 (±4.1) 0.03 1.1 2.5 2.1 

Hawaii ................... 78.7 (±5.5) 0.04 79.6 (±5.9) 0.04 81.2 (±5.5) 0.03 80.9 (±5.5) 0.03 0.8 2.5 2.1 

Idaho .................... 69.4 (±5.9) 0.04 70.2 (±6.8) 0.05 75.0 (±5.6) 0.04 74.3 (±5.6) 0.04 0.8 5.7 4.9 

Illinois ................... 78.6 (±4.3) 0.03 81.3 (±4.3) 0.03 82.3 (±3.9) 0.02 81.7 (±4.0) 0.03 2.8 3.8 3.1 

Indiana .................. 76.0 (±4.8) 0.03 77.8 (±5.2) 0.03 80.4 (±4.6) 0.03 79.8 (±4.6) 0.03 1.8 4.4 3.8 

Iowa .................... 78.7 (±5.5) 0.04 80.7 (±5.8) 0.04 82.1 (±5.3) 0.03 81.7 (±5.4) 0.03 2.0 3.5 3.0 

Kansas .................. 66.8 (±6.8) 0.05 70.6 (±7.2) 0.05 72.0 (±6.9) 0.05 70.2 (±6.9) 0.05 3.8 5.2 3.4 

Kentucky ................. 72.3 (±6.3) 0.04 75.1 (±6.7) 0.05 76.5 (±6.1) 0.04 76.3 (±6.1) 0.04 2.8 4.2 4.0 

Louisiana ................. 66.8 (±5.6) 0.04 70.8 (±5.8) 0.04 72.2 (±5.4) 0.04 71.5 (±5.4) 0.04 4.0 5.4 4.6 

Maine ................... 80.7 (±5.1) 0.03 82.3 (±6.5) 0.04 85.1 (±4.9) 0.03 84.3 (±5.0) 0.03 1.6 4.3 3.5 

Maryland ................. 78.7 (±5.6) 0.04 81.3 (±5.7) 0.04 81.2 (±5.5) 0.03 81.2 (±5.5) 0.03 2.5 2.5 2.5 

Massachusetts .............. 86.2 (±3.8) 0.02 86.3 (±4.4) 0.03 87.5 (±3.9) 0.02 87.4 (±3.9) 0.02 0.1 1.3 1.2 

Michigan ................. 81.6 (±4.3) 0.03 82.1 (±5.5) 0.03 85.7 (±3.7) 0.02 85.2 (±3.8) 0.02 0.5 4.1 3.6 

Minnesota ................. 76.8 (±6.5) 0.04 78.6 (±7.0) 0.05 80.6 (±6.6) 0.04 80.5 (±6.6) 0.04 1.8 3.8 3.7 

Mississippi ................ 75.7 (±6.3) 0.04 76.6 (±7.2) 0.05 79.3 (±6.1) 0.04 79.3 (±6.1) 0.04 0.9 3.6 3.6 

Missouri .................. 73.0 (±6.5) 0.05 75.4 (±7.2) 0.05 77.0 (±6.5) 0.04 76.8 (±6.5) 0.04 2.4 3.9 3.8 

Montana .................. 66.6 (±6.5) 0.05 68.1 (±7.0) 0.05 70.7 (±6.4) 0.05 70.1 (±6.5) 0.05 1.4 4.1 3.5 

Nebraska ................. 78.2 (±5.3) 0.03 80.3 (±5.3) 0.03 80.7 (±5.1) 0.03 80.7 (±5.1) 0.03 2.1 2.5 2.5 

Nevada .................. 76.4 (±6.1) 0.04 79.1 (±6.7) 0.04 81.4 (±5.8) 0.04 81.0 (±5.8) 0.04 2.7 5.1 4.6 

New Hampshire ............. 83.5 (±5.0) 0.03 83.4 (±5.9) 0.04 85.0 (±4.9) 0.03 85.0 (±4.9) 0.03 –0.1 1.5 1.4 

New Jersey ................ 76.1 (±5.4) 0.04 78.5 (±5.6) 0.04 79.9 (±5.1) 0.03 79.4 (±5.1) 0.03 2.4 3.8 3.2 

New Mexico ............... 64.6 (±6.8) 0.05 63.2 (±7.5) 0.06 65.9 (±6.8) 0.05 65.9 (±6.8) 0.05 –1.4 1.3 1.2 

New York . . . . . . . . . . . . . . . . . 77.5 (±4.3) 0.03 78.6 (±6.1) 0.04 82.0 (±4.0) 0.03 81.4 (±4.1) 0.03 1.1 4.4 3.9 

North Carolina .............. 82.4 (±5.3) 0.03 85.6 (±5.4) 0.03 86.2 (±4.8) 0.03 86.2 (±4.8) 0.03 3.2 3.8 3.8 

North Dakota ............... 77.7 (±6.1) 0.04 80.7 (±5.9) 0.04 82.2 (±5.3) 0.03 81.9 (±5.3) 0.03 3.0 4.5 4.2 

Ohio .................... 75.0 (±4.4) 0.03 75.9 (±5.8) 0.04 79.2 (±4.2) 0.03 78.5 (±4.3) 0.03 0.8 4.2 3.4 

Oklahoma ................. 65.3 (±7.4) 0.06 68.7 (±9.7) 0.07 75.6 (±7.3) 0.05 74.7 (±7.4) 0.05 3.4 10.3 9.4 

Oregon .................. 70.0 (±5.8) 0.04 73.9 (±6.2) 0.04 74.9 (±5.8) 0.04 74.5 (±5.8) 0.04 3.9 4.9 4.6 

Pennsylvania ............... 74.7 (±5.4) 0.04 74.6 (±8.4) 0.06 79.4 (±5.6) 0.04 78.5 (±5.4) 0.04 –0.2 4.7 3.8 

Rhode Island ............... 84.5 (±5.6) 0.03 86.2 (±5.6) 0.03 86.3 (±5.4) 0.03 86.3 (±5.4) 0.03 1.7 1.8 1.8 

South Carolina .............. 78.8 (±6.3) 0.04 79.1 (±7.7) 0.05 81.8 (±6.4) 0.04 81.9 (±6.3) 0.04 0.3 3.1 3.1 

South Dakota .............. 79.9 (±6.4) 0.04 81.6 (±6.8) 0.04 82.7 (±6.4) 0.04 82.7 (±6.4) 0.04 1.7 2.8 2.8 

Tennessee ................ 78.2 (±4.1) 0.03 82.1 (±4.2) 0.03 84.0 (±3.6) 0.02 83.0 (±3.8) 0.02 3.9 5.8 4.7 

Texas ................... 67.9 (±5.1) 0.04 67.2 (±6.7) 0.05 72.9 (±5.5) 0.04 72.5 (±5.5) 0.04 –0.6 5.0 4.7 

Utah .................... 75.7 (±5.8) 0.04 78.4 (±6.3) 0.04 80.0 (±5.6) 0.04 80.0 (±5.6) 0.04 2.6 4.3 4.3 

Vermont .................. 80.9 (±4.8) 0.03 79.3 (±6.0) 0.04 82.4 (±4.6) 0.03 81.9 (±4.7) 0.03 –1.6 1.6 1.0 

Virginia .................. 72.0 (±6.1) 0.04 77.7 (±6.1) 0.04 78.9 (±5.8) 0.04 78.3 (±5.8) 0.04 5.7 6.9 6.3 

Washington ................ 69.2 (±4.8) 0.04 72.2 (±5.5) 0.04 76.3 (±4.5) 0.03 75.9 (±4.5) 0.03 3.0 7.1 6.7 

West Virginia ............... 76.9 (±6.2) 0.04 77.6 (±7.2) 0.05 79.6 (±6.1) 0.04 78.8 (±6.2) 0.04 0.8 2.8 1.9 

Wisconsin ................. 80.3 (±4.3) 0.03 85.4 (±3.5) 0.02 85.4 (±3.4) 0.02 85.0 (±3.5) 0.02 5.1 5.1 4.8 

Wyoming ................. 73.3 (±6.4) 0.04 76.8 (±7.3) 0.05 80.1 (±5.8) 0.04 79.2 (±5.7) 0.04 3.4 6.8 5.8 

1CI is half-width of 95-percent confidence interval.

2CV is coefficient of variation (standard error/estimate).

3Shot cards and provider records do not agree on the number of doses administered for each of the following vaccines: diphtheria, tetanus toxoids, and acellular pertussis (DTaP); polio; measlesmumps-rubella (MMR); Haemophilus influenzae type b (Hib); hepatitis B (Hep B); and varicella (VRC).

NOTE: 4:3:1:3:3 refers to 4 or more doses of diphtheria and tetanus toxoids and pertussis vaccine (DTP), 3 or more doses of polio vaccine (polio), 1 or more doses of measles-containing vaccine

(MCV), 3 or more doses of Haemophilus influenzae type b vaccine (Hib), and 3 or more doses of hepatitis B vaccine (Hep B).
Series 2, No. 138 [ Page 53 

Appendix 

National Immunization Survey 

Immunization History Questionnaire 
Page 54 [ Series 2, No. 138 
Series 2, No. 138 [ Page 55 
Page 56 [ Series 2, No. 138 
Vital and Health Statistics 

series descriptions 

SERIES 1. 

SERIES 2. 

SERIES 3. 

SERIES 4. 

SERIES 5. 

SERIES 6. 

SERIES 10. 

SERIES 11. 

SERIES 12. 

SERIES 13. 

Programs and Collection Procedures —These reports 

describe the data collection programs of the National Center 

for Health Statistics. They include descriptions of the methods 

used to collect and process the data, definitions, and other 

material necessary for understanding the data. 

Data Evaluation and Methods Research—These reports 

are studies of new statistical methods and include analytical 

techniques, objective evaluations of reliability of collected 

data, and contributions to statistical theory. These studies 

also include experimental tests of new survey methods and 

comparisons of U.S. methodology with those of other 

countries. 

Analytical and Epidemiological Studies—These reports 

present analytical or interpretive studies based on vital and 

health statistics. These reports carry the analyses further than 

the expository types of reports in the other series. 

Documents and Committee Reports—These are final 

reports of major committees concerned with vital and health 

statistics and documents such as recommended model vital 

registration laws and revised birth and death certificates. 

International Vital and Health Statistics Reports—These 

reports are analytical or descriptive reports that compare U.S. 

vital and health statistics with those of other countries or 

present other international data of relevance to the health 

statistics system of the United States. 

Cognition and Survey Measurement—These reports are 

from the National Laboratory for Collaborative Research in 

Cognition and Survey Measurement. They use methods of 

cognitive science to design, evaluate, and test survey 

instruments. 

Data From the National Health Interview Survey—These 

reports contain statistics on illness; unintentional injuries; 

disability; use of hospital, medical, and other health services; 

and a wide range of special current health topics covering 

many aspects of health behaviors, health status, and health 

care utilization. They are based on data collected in a 

continuing national household interview survey. 

Data From the National Health Examination Survey, the 

National Health and Nutrition Examination Surveys, and 

the Hispanic Health and Nutrition Examination Survey— 

Data from direct examination, testing, and measurement on 

representative samples of the civilian noninstitutionalized 

population provide the basis for (1) medically defined total 

prevalence of specific diseases or conditions in the United 

States and the distributions of the population with respect to 

physical, physiological, and psychological characteristics, and 

(2) analyses of trends and relationships among various 

measurements and between survey periods. 

Data From the Institutionalized Population Surveys— 

Discontinued in 1975. Reports from these surveys are 

included in Series 13. 

Data From the National Health Care Survey—These 

reports contain statistics on health resources and the public’s 

use of health care resources including ambulatory, hospital, 

and long-term care services based on data collected directly 

from health care providers and provider records. 

SERIES 14. Data on Health Resources: Manpower and Facilities— 

Discontinued in 1990. Reports on the numbers, geographic 

distribution, and characteristics of health resources are now 

included in Series 13. 

SERIES 15. Data From Special Surveys —These reports contain 

statistics on health and health-related topics collected in 

special surveys that are not part of the continuing data 

systems of the National Center for Health Statistics. 

SERIES 16. Compilations of Advance Data From Vital and Health 

Statistics—Advance Data Reports provide early release of 

information from the National Center for Health Statistics’ 

health and demographic surveys. They are compiled in the 

order in which they are published. Some of these releases 

may be followed by detailed reports in Series 10–13. 

SERIES 20. Data on Mortality—These reports contain statistics on 

mortality that are not included in regular, annual, or monthly 

reports. Special analyses by cause of death, age, other 

demographic variables, and geographic and trend analyses 

are included. 

SERIES 21. Data on Natality, Marriage, and Divorce—These reports 

contain statistics on natality, marriage, and divorce that are 

not included in regular, annual, or monthly reports. Special 

analyses by health and demographic variables and 

geographic and trend analyses are included. 

SERIES 22. Data From the National Mortality and Natality Surveys— 

Discontinued in 1975. Reports from these sample surveys, 

based on vital records, are now published in Series 20 or 21. 

SERIES 23. Data From the National Survey of Family Growth—These 

reports contain statistics on factors that affect birth rates, 

including contraception, infertility, cohabitation, marriage, 

divorce, and remarriage; adoption; use of medical care for 

family planning and infertility; and related maternal and infant 

health topics. These statistics are based on national surveys 

of women of childbearing age. 

SERIES 24. Compilations of Data on Natality, Mortality, Marriage, and 

Divorce—These include advance reports of births, deaths, 

marriages, and divorces based on final data from the National 

Vital Statistics System that were published as National Vital 

Statistics Reports (NVSR), formerly Monthly Vital Statistics 

Report. These reports provide highlights and summaries of 

detailed data subsequently published in Vital Statistics of the 

United States. Other special reports published here provide 

selected findings based on final data from the National Vital 

Statistics System and may be followed by detailed reports in 

Series 20 or 21. 

For answers to questions about this report or for a list of reports published 

in these series, contact: 

Information Dissemination Staff 

National Center for Health Statistics 

Centers for Disease Control and Prevention 

3311 Toledo Road, Room 5412 

Hyattsville, MD 20782 

1-866-441-NCHS (6247)

E-mail: nchsquery@cdc.gov

Internet: www.cdc.gov/nchs
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DHHS Publication No. (PHS) 2005-1338, Series 2, No. 138 

04-0581 (3/2005)