Series 1, Number 40

Design and Operation of the

National Survey of Early

Childhood Health, 2000

Program and Collection Procedures

DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Disease Control and Prevention

National Center for Health Statistics

Hyattsville, Maryland

June 2002

DHHS Publication No. (PHS) 2002-1316
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

Blumberg SJ, Olson L, Osborn L, et al. Design and operation of the National

Survey of Early Childhood Health, 2000. National Center for Health Statistics.

Vital Health Stat 1(40). 2002

Library of Congress-in-Publication Data

Design and operation of the national survey of early childhood health, 2000

p. cm.— (Vital and health statistics. Ser. 1, Programs and collection

procedures ; no. 040) (DHHS publication; no. (PHS) 2002-1316)

ISBN 0-8406-0580-3

1. Children—Health and hygiene—United States—Statistics. 2. Child health

services—United States—Statistics. 3. Medical care surveys—United States.

I. National Center for Health Statistics (U.S.) II. Series. III. Series: DHHS

publication ; no. (PHS) 2002-1316

RA407.3 .D45 2002

613’.0432’0973021—dc21

2002023513

For sale by the U.S. Government Printing Office

Superintendent of Documents

Mail Stop: SSOP

Washington, DC 20402-9328

Printed on acid-free paper.
National Center for Health Statistics

Edward J. Sondik, Ph.D., Director

Jack R. Anderson, Deputy Director

Jack R. Anderson, Acting Associate Director for

International Statistics

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

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

and Methodology

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

Analysis, Epidemiology, and Health Promotion

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

and Legislation

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

Vital and Health Statistics Systems

Douglas L. Zinn, Acting Associate Director for

Management

Charles J. Rothwell, Associate Director for Information

Technology and Services

Division of Health Interview Statistics

Jane F. Gentleman, Ph.D., Director

Anne K. Stratton, M.S., Associate Director for Planning and

Production

Eve Powell-Griner, Ph.D., Associate Director for Science

Susan S. Jack, M.S., Special Assistant for Data Quality and

User Services

Eve Powell-Griner, Ph.D., Acting Chief, Illness and

Disability Statistics Branch

Howard Riddick, Ph.D., Chief, Survey Planning and

Development Branch

Robert A. Hill, Chief, Systems and Programming Branch

Robert A. Wright, Chief, Utilization and Expenditure

Statistics Branch

Acknowledgments

The National Survey of Early

Childhood Health (NSECH) was

sponsored by the American Academy of

Pediatrics and was made possible with

funding from The Gerber Foundation.

Additional funding was provided by the

Maternal and Child Health Bureau of

the Health Resources and Services

Administration and by the American

Academy of Pediatrics Friends of

Children Fund. The principal

investigator is Lynn Olson, Ph.D.

The survey was conducted by the

National Center for Health Statistics

(NCHS) of the Centers for Disease

Control and Prevention (CDC). The

project director is Marcie Cynamon.

The University of California, Los

Angeles (UCLA), Center for Healthier

Children, Families, and Communities,

and the National Center for Infancy and

Early Childhood Health Policy at UCLA

contributed to the design of the

questionnaire and the study. The

principal investigator is Neal Halfon,

M.D., M.P.H. Additional design

assistance was provided by the

American Academy of Pediatrics,

NCHS, and the Foundation for

Accountability. The National

Immunization Program of CDC

graciously permitted the use of the

National Immunization Survey sampling

frame for this survey.
Contents

Abstract ................................................................................................ 1

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

The National Immunization Survey .......................................................................... 1

The State and Local Area Integrated Telephone Survey .......................................................... 1

Key Features of the National Survey of Early Childhood Health .................................................. 2

Background ............................................................................................... 2

Sample Design............................................................................................. 3

Sample Selection ......................................................................................... 3

Drawing the National Immunization Survey Sample ............................................................ 3

The National Survey of Early Childhood Health Sample Allocation ................................................ 3

Questionnaire .............................................................................................. 4

Computer-Assisted Telephone Interviewing Programming ........................................................ 5

Spanish Version .......................................................................................... 6

Pretest of Survey Instrument................................................................................ 6

Survey Operations .......................................................................................... 6

Interviewer Training ...................................................................................... 6

Advance Letter .......................................................................................... 6

Informed Consent ........................................................................................ 6

Assurance of Confidentiality................................................................................ 7

Interview Length ......................................................................................... 7

Other Languages ......................................................................................... 7

Toll-Free Telephone Number ............................................................................... 7

Cases Pending at the Close of Data Collection ................................................................. 8

Break-offs and Refusals ................................................................................... 8

Response Rates .......................................................................................... 8

Efforts to Maximize Response Rates ......................................................................... 9

Data Files................................................................................................. 9

Editing ................................................................................................. 9

Imputation ............................................................................................. 10

Edits to Protect Confidentiality............................................................................. 10

Additional Edits......................................................................................... 11

Dummy Variables ....................................................................................... 11

Estimation Procedures...................................................................................... 11

Base Sampling Weight ................................................................................... 11

Households with Multiple Telephone Lines................................................................... 12

The First Form of Nonresponse: Unknown Household Status .................................................... 12

Separation of the Telephone Lines Into the Main Sample and the Oversample ...................................... 12

The Second Form of Nonresponse: Unknown Household Eligibility............................................... 13

Adjustment for Subsampling in the Oversample ............................................................... 13

The Third Form of Nonresponse: Eligible Households Who Do Not Complete the Interview........................... 13

The Child-Level Weight .................................................................................. 14

iii
Poststratification ........................................................................................ 14

Interpretation of Weighted Estimates ........................................................................ 15

Variance Estimation and Hypothesis Testing .................................................................. 15

Variance Estimation Using SUDAAN ....................................................................... 15

Variance Estimation Using STATA.......................................................................... 15

Quality Control ........................................................................................... 15

Quality Control of Interviewing ............................................................................ 15

Sample Monitoring and Quality Control ..................................................................... 16

Data Quality Control ..................................................................................... 16

Estimation Quality Control ................................................................................ 16

Guidelines for Data Use .................................................................................... 16

References ............................................................................................... 16

Appendix I

Sampling and Sampling Weights Technical Summary ............................................................ 18

Sampling Design ........................................................................................ 18

Drawing the National Immunization Survey Sample ........................................................... 18

National Survey of Early Childhood Health Sample Allocation................................................... 19

Sample Selection ........................................................................................ 20

Sample Weights......................................................................................... 21

Base Sampling Weight ................................................................................... 21

Multiple-Telephone Households ............................................................................ 21

Unit Nonresponse Adjustment 1 (Residental Status Unknown) ................................................... 21

Unit Nonresponse Adjustment 2 (Households of Unknown Eligibility)............................................. 21

Subsampling Adjustment.................................................................................. 22

An Example of Subsampling Adjustment .................................................................... 23

Unit Nonresponse Adjustment 3 (Nonresponse by Eligible Households)............................................ 23

Adjustment of Household Weights to Known Control Totals..................................................... 23

Child Weights .......................................................................................... 23

Adjustment for Noncoverage of Nontelephone Households ...................................................... 23

Poststratification ........................................................................................ 24

Appendix II

Related Survey Content and Sources of Questions ............................................................... 26

Appendix III

Computer-Assisted Telephone Interviewing Specifications......................................................... 35

Appendix IV

Advance Letter ........................................................................................... 91

Appendix V

Disposition Code Frequencies and Response Rate Calculations..................................................... 92

iv
Objectives

This report presents the Design and Operation of the

development, plan, and operation of the

National Survey of Early Childhood National Survey of Early Health, a module of the State and Local

Area Integrated Telephone Survey,

conducted by the National Center for Childhood Health, 2000

Health Statistics, Centers for Disease

Control and Prevention. This survey Stephen J. Blumberg, Ph.D., Centers for Disease Control and

was designed to assess parents’

perceptions of their children’s pediatric Prevention and Lorayn Olson, Ph.D.; Larry Osborn, M.P.H.; K. P.

care. In addition, data were collected Srinath, Ph.D.; and Holly Harrison, M.A., Abt Associates Inc.

that can be used to examine

relationships between the promotion of

health in the pediatric office and Introduction States and local areas called

promotion of health in the home. Immunization Action Plan (IAP) areas,

Funding for the survey was provided by which encompassed the entire United

The Gerber Foundation, the American The National Survey of Early States. These grants were targeted

Academy of Pediatrics, and the Childhood Health (NSECH) toward improving vaccination levels of

Maternal and Child Health Bureau, detailed in this report was children by age 2. The National

Health Resources and Services

Administration. The UCLA Center for designed to collect data regarding Immunization Program at CDC manages

Healthier Children, Families, and parents’ perceptions of their children’s these grants. NIS was established to

Communities contributed to the design pediatric care, and to examine monitor the use of these grant funds and

of the study and the questionnaire. relationships between the promotion of to monitor the vaccination levels of very

health in the pediatric office and young children within the IAP areas and

Methods promotion of health in the home. This across the United States. (1)

A national random-digit-dialed (RDD) survey was conducted as a module of With respect to data collection, the

sample of households with children the State and Local Area Integrated NIS presents an extraordinary challenge.

4–35 months of age was selected. The Telephone Survey (SLAITS), which uses The survey must screen an extremely

study included an oversample of the same sampling frame as the Centers large number of households to find its

households having an eligible black for Disease Control and Prevention’s relatively rare target population of

non-Hispanic or Hispanic child. In (CDC) National Immunization Survey households with children between 19–35

households with more than one eligible (NIS). months of age. Each year, nearly 1

child, one was randomly selected to be million households are screened by

the subject of the interview. The telephone to obtain 34,000 completed respondent was the parent or guardian The National household interviews. Fortunately, the

who was most responsible for the

child’s health care. A computer-assisted Immunization Survey large initial sample of telephone

telephone interviewing (CATI) system Though State laws requiring

numbers in the NIS provides a

was used to collect the data. cost-effective opportunity to survey children to be vaccinated before entering other populations in addition to the rare

school were thought to result in high population that eventually screens into Results vaccination rates in the school-age the NIS. A total of 2,068 interviews were population, as of the early 1990s

completed during the first half of 2000. preschool children in the United States

The response rate was 65.6%. A data were not adequately vaccinated against The State and Local Area file has been released that contains preventable diseases. This shortfall

demographic information on the focal became evident according to a variety of Integrated Telephone

child and respondent, substantive

health and health-related data, and different measures. To address the Survey

sampling weights. Estimates based on problem, grants were awarded to 78 The survey mechanism that uses the

the sampling weights generalize to the NIS sample frame for collecting data

entire

months of age. Childhood Health c State and Local as SLAITS. The SLAITS program,

Area Integrated Telephone Survey c sponsored by the National Center for

pediatric care c health provider Health Statistics (NCHS), CDC, is a

contacts c quality of care c child broad-based, ongoing surveillance

development system available at State and local

U.S. population of children 4–35 Keywords: National Survey of Early about these other populations is known

Page 1
Page 2 [ Series 1, No. 40

levels for tracking and monitoring the

health and well-being of children and

adults. It began in 1997 with a pilot test

in two States—Iowa and Washington—

with a series of questions on health,

including issues of access to care, health

status, and insurance. In 1998, a

SLAITS module concerning child

well-being and welfare issues was

implemented using three samples: A

general Texas sample, known Medicaid

program participants in Texas, and

known Medicaid and MinnesotaCare

program participants in Minnesota.

The survey detailed in this report is

the third study in the SLAITS series.

Key Features of the

National Survey of Early

Childhood Health

+ Use of the first two calendar

quarters of the NIS random-digitdial (RDD) sampling frame for 2000

+ Questionnaire to collect data on one

child regarding: Health care

utilization; parental perceptions of

pediatric care; interactions with

health care providers; family

interactions and home safety;

parental and child health; financial

welfare and health insurance; and

demographic and household

information

+ Computer-assisted telephone

interview (CATI) instrument

+ An average interview length of

approximately 30 minutes

+ One child 4–35 months of age

randomly selected from households

with age-eligible children to be the

target of the interview

+ Respondent is the adult household

member who is primarily

responsible for the sampled child’s

medical care

+ Over 2,000 completed interviews

(more than 1,200 interviews in a

national sample, plus an oversample

of more than 800 black nonHispanic or Hispanic children)

+ NIS screener and interview

completed before the SLAITS

portion of the interview

+ Households requiring the

administration of the screener and/or

interview in Spanish included

through the use of a Spanish

translation of the questionnaire

administered by bilingual

interviewers

+ Survey estimates include a weight

adjustment strategy to allow for the

representation of households without

telephones

Background

Before they reach age 3, most

children in the United States will

have seen a doctor 12 times for

routine and sick visits. As a result,

pediatricians and other health care

providers are in a critical position to

identify developmental issues for

children within their care and to

disseminate information to parents.

Despite this opportunity, however, there

is little research that seeks to gain

information on pediatric care from the

parents’ perspective. NSECH was

designed to collect that information.

Two recent national surveys have

examined parental concerns, needs, and

expectations surrounding the

development of their children. In the

Zero to Three Survey of Parents,

sponsored by the nonprofit National

Center for Infants, Toddlers, and

Families, the data showed that parents

were unsure about their specific role in

their child’s development, although they

recognized their importance in the

process. In the Survey of Parents of

Young Children, sponsored by the

Commonwealth Fund, parents reported

that they received very little guidance

on such topics as how to discipline their

child, how to encourage their child to

learn, and how to deal with their child’s

sleeping patterns. Combined, these

surveys suggest that there is a need and

demand for information, guidance, and

interventions to help ensure the optimal

development of children.

In surveys conducted by the

American Academy of Pediatrics,

pediatricians agreed that early

intervention programs are important in

promoting children’s development and

improving parents’ understanding of

development issues. These surveys also

suggest that pediatricians routinely

assess children’s developmental

milestones and parental concerns

regarding development. Still,

pediatricians had significant concerns

about the economic feasibility of

providing such developmental services

in the context of their pediatric

practices.

NSECH sought to determine the

primary issues and concerns that parents

of young children face, the degree to

which parents believe that these issues

and worries should be addressed by

pediatricians, and the extent to which

they are presently being addressed.

Previous surveys of parents have

demonstrated that parents can provide

reliable data on developmental services

received and that these data can be used

to evaluate the performance of health

care systems in the promotion of the

healthy development of young children

(2).

The major research questions

addressed by the NSECH were:

+ What are the concerns of parents

and what are the health care needs

of young children?

+ Are these health care needs and

these parental concerns being

addressed when children visit health

care providers?

+ What is the quality of

developmental and psychosocial care

that young children receive?

+ What factors are associated with the

receipt of better quality, more

comprehensive pediatric care?

+ What is the prevalence of selected

home health behaviors in early

childhood?

+ What is the relationship between

parental/home health behaviors and

experiences with pediatric health

care delivery?

The primary purpose of the survey,

as indicated by the research questions,

was to characterize the content of care

and the parent’s (and child’s)

experiences with pediatric preventive

health care. This preventive health care

can be provided by any pediatric health
Series 1, No. 40 [ Page 3

care providers (broadly defined) and is

not limited to care provided by

pediatricians, pediatric specialists, or

medical doctors. The second purpose of

the study was to assist in understanding

the relationship between the promotion

of health in the pediatric office and

promotion of health in the home.

Sample Design

As mentioned, SLAITS is a

program of surveys designed to

take advantage of the large

number of screening calls required for

the CDC surveillance study, the NIS.

Sample Selection

Each quarter NIS selects a random

sample of telephone numbers in each of

78 IAP areas (including the District of

Columbia and 27 other urban areas) that

cover the United States. NIS screens

these samples to identify households

that contain children 19–35 months of

age and interviews a household

respondent about each age-eligible

child’s immunization history and the

demographic characteristics of the

household. With consent, NIS then

contacts the immunization providers of

those children (in a mail survey) to

obtain vaccination information from the

child’s medical record, to compensate

for possible biases in the vaccination

information reported by households.

Because the data from providers are the

primary basis for estimates of

vaccination coverage, the target sample

sizes are designed to yield

approximately the same number of

children with provider data in each IAP

area. Those sample sizes vary among

IAP areas, in response to the NIS’

experience in completing household

interviews and obtaining data from

providers.

NSECH used the NIS sample to

investigate parental perceptions of

pediatric care for children age 4–35

months of age. The goal was to

complete at least 2,000 interviews for

children in this age range and to collect

enough data on black non-Hispanic and

Hispanic children to yield precise

estimates. To accomplish this, a random

subsample of the NIS sample was

selected and telephone numbers were

randomly designated for either an

NSECH national sample or for an

NSECH oversample. The oversample

was designed to collect data only from

those households with an age-eligible

Black non-Hispanic or Hispanic child.

Regardless of the NSECH sample

for which the telephone numbers were

selected, all telephone numbers

designated for NSECH were selected

from the numbers randomly generated

for the NIS sample. Further, when these

telephone numbers were first called,

identified households were screened for

NIS before screening for NSECH.

Therefore, the procedures for drawing

the NIS sample were the first steps in

the procedures for drawing the NSECH

sample.

The next two sections describe the

basic NIS sample design and the

NSECH sample allocation procedures.

These sections are intended to serve as a

nontechnical description of the NSECH

sample design procedures. Appendix I

includes a more technical description of

the NSECH sample design and

weighting plan. For more detail on the

NIS sample design, readers are

encouraged to obtain chapter 3 of the

1999 NIS Sample Design Report (3),

which is available from NCHS.

Drawing the National

Immunization Survey

Sample

Each quarter NIS screens a sample

of households in each of the 78 IAP

areas, which cover the 50 States and 28

metropolitan areas, to identify

households that contain at least one

child between 19–35 months of age.

Because only 5% of households in the

United States contain children between

19–35 months of age, a large number of

households are screened to identify

households with eligible children.

Households are selected for screening

through list-assisted RDD. This

sampling method involves selecting

telephone numbers at random from the

frame of all possible telephone numbers.

In the United States, telephone

numbers consist of an area code (3

digits), a prefix or exchange (3 digits),

and a suffix (4 digits). A random sample

of telephone numbers can be chosen by

randomly selecting an area code and

prefix combination currently in use and

appending a four-digit number chosen

randomly between 0000 and 9999. This

sample is a simple random sample of

telephone numbers from the frame of all

possible telephone numbers. Before the

selection of the sample of telephone

numbers, banks of 100 consecutive

numbers in the same area code and

prefix combination that contain zero

directory-listed telephone numbers—that

is, banks of 100 numbers that have a

low probability of containing working

residential numbers—are deleted from

the sampling frame. For this step, the

GENESYS Sampling System (a

proprietary product of Marketing

Systems Group) uses a file of

directory-listed residential numbers from

Donnelley Marketing Information

Services (DMIS). As indicated earlier, a

simple random sample of 10-digit

telephone numbers is then drawn from

the retained banks of 100 numbers and

residential numbers are identified by

calling these numbers.

In each IAP area, the number of

households that needs to be screened is

calculated first based on the required

sample size and using the expected

eligibility rate for the IAP area, and then

the number of telephone numbers that

need to be called is computed using the

expected working residential number

rate. The number of telephone numbers

drawn is increased to compensate for

the fact that not all respondents will

agree to participate and therefore there

will be some degree of nonresponse.

The National Survey of

Early Childhood Health

Sample Allocation

Main Sample—For NIS, the goal is to

generate a sample that will be

representative of the IAP-specific

population of children 19–35 months of

age and to generate a sufficient sample

to permit an equivalent number of

completed interviews from each IAP. In
Page 4 [ Series 1, No. 40

contrast, for the main sample of the

NSECH, the goal was to generate a

sample representative of the national

population of children 4–35 months of

age. To do so, equal size samples were

not drawn from every geographic area,

because this allocation would yield too

many children in some States and not

enough children from other States.

Rather, samples were drawn from each

geographic area in rough proportion to

the number of young children in each

area. This way, for example, more

telephone numbers were selected from

Los Angeles than from Wyoming,

because the Los Angeles population

includes more young children than does

the Wyoming population.

From NIS, estimates were obtained

of the approximate number of telephone

lines to be called in each geographic

area to find each household with an

age-eligible child. In some geographic

areas, more telephone numbers must be

sampled to find each child. Therefore,

even when the goal was to sample the

same number of children in two

geographic areas, more telephone

numbers may have been sampled in one

area than in another.

The end result was that randomly

generated telephone numbers were

selected in such a way that every young

child selected to participate in the

survey represented approximately the

same number of young children not

selected to participate in the survey, and

that the young children selected were

randomly distributed across the country

in the same proportion that all young

children are distributed across the

country.

Each selected telephone number

was then called, and if it belonged to a

household, the person answering the

telephone was asked if there were any

children under 3 years of age living or

staying in the household. If NIS

age-eligible children were in the

household, the NIS interview was

conducted before the NSECH interview.

Otherwise, the interviewer asked for the

birth dates of all children living or

staying in the household who were

under 3 years of age. In households with

more than one NSECH age-eligible

child, one was randomly selected for the

interview.

As with all sample surveys, random

sampling error could result in finding

more or fewer children than expected in

one geographic area. This minor

imbalance is adjusted when the

sampling weights are generated.

Oversample—Likewise, the goal of the

oversample was to generate a sample

representative of the national population

of black non-Hispanic or Hispanic

children 4–35 months of age. (For

reading ease, these children are referred

to as minority children, though this

population is not inclusive of all

minority races and ethnicities.) As

before, equal size samples were not

drawn from every geographic area,

because then the sample would include

too many minority children from States

with few minority children and not

enough children from States with a large

number of minority children. So,

samples were drawn from each

geographic area in rough proportion to

the number of minority young children

in each area.

All prefix areas, regardless of their

minority status, were eligible for the

oversample. However, randomly

generated telephone numbers from these

telephone banks were selected so that

more telephone numbers were selected

from geographic areas with more young

minority children and fewer telephone

numbers were selected from geographic

areas with fewer young minority

children.

Again, from the NIS, estimates

were obtained of the approximate

number of telephone lines to be called

in each geographic area to find each

household with an age-eligible minority

child. Therefore, more telephone

numbers may have been sampled in one

area than in another.

The end result was that randomly

generated telephone numbers were

selected in such a way that every young

minority child selected to participate in

the survey represented approximately

the same number of young minority

children not selected to participate in the

survey in each IAP area, and that the

young minority children selected were

randomly distributed across the country

in approximately the same proportion

that all young minority children are

distributed across the country. (It should

be noted that the sample allocation for

the oversample was not a true

proportional allocation. Instead, the

allocation was modified slightly to

reduce the number of screening

interviews required to reach a household

with age-eligible black non-Hispanic or

Hispanic children. See appendix I.)

Each selected telephone number

was then called, and if it belonged to a

household, the person answering the

telephone was asked if there were any

NIS age-eligible children living in the

household. If NIS age-eligible children

were in the household, the NIS

interview was conducted first.

Otherwise, the interviewer asked for the

birth dates, race, and ethnicity of all

children living or staying in the

household who were under 3 years of

age. If young minority children lived in

the household, one was randomly

selected for the interview.

Random sampling error could result

in finding more or fewer minority

children than expected in one

geographic area. This minor imbalance

is adjusted when the sampling weights

are generated.

Because some geographic areas

have very small minority populations

(e.g., Iowa), very few randomly

generated telephone numbers may have

been selected in these areas for the

minority oversample. And because of

random sampling error, it is possible

that young minority children were not

identified in some areas. But telephone

numbers for the minority oversample

were called in every geographic area.

Questionnaire

The NSECH questionnaire includes

questions from a variety of other

studies. These include surveys

from the Foundation for Accountability

(e.g., the Promoting Healthy

Development Survey and the Promoting

Healthy Development Survey Plus), the

Commonwealth Fund (e.g., the Pediatric

Developmental Services Survey and the

Survey of Families with Young

Children), the Institute for Social

Research at the University of Michigan
Series 1, No. 40 [ Page 5

(e.g., the Panel Study of Income

Dynamics Child Development

Supplement), NCHS (e.g., the National

Health Interview Survey and the

National Survey of Children with

Special Health Care Needs), and other

Federal agencies (e.g., the Consumer

Assessment of Health Plans Survey, the

Early Childhood Longitudinal Survey,

and the Medical Expenditure Panel

Survey). The correspondence of NSECH

items to other surveys is listed in

appendix II.

The NSECH questionnaire was

designed to immediately follow a

completed NIS interview in households

with an NIS-eligible child or the NIS

screener in households without an

NIS-eligible child. The questionnaire

was divided into seven parts,

summarized in this section, and

provided in appendix III. Questions

were answered by the parent or guardian

who was primarily responsible for the

sample child’s medical care.

Health Care Utilization—This section

addressed the number of visits made to

a health care provider, provider

demographics, and how providers were

initially identified.

Parental Perception of Pediatric

Care—This section assessed the length

of the last visit to a health care provider,

whether the parent asked all the

questions he or she wanted to ask at that

visit, rating of the quality of the visit on

a 10-point scale, and a general

description of the child’s health.

Interactions with Health Care

Providers—In this section, the majority

of the questions were age-specific, with

the age of the sampled child

determining questions to be asked. The

age ranges were defined as 4–10, 11–18,

and 19–35 months old. For the youngest

children, between 4–10 months,

questions were asked about breastfeeding, the introduction of solid foods

into the diet, sleeping positions, burn

prevention, car seat use, childcare, and

immunizations. For older children,

questions focused on food and feeding,

sleeping with a bottle, weaning the child

from the bottle, guidance and discipline,

toilet training, reading to the child, and

bedtime routines. Additional questions

asked in all age groups examined the

style and level of attention given by the

health care provider, the environment in

which the child is being reared,

developmental issues, birthing and

parenting classes, and questions about

the child’s infancy and birth.

Family Interactions and Home

Safety—This section addressed the level

of interaction that occurs between the

child and other family members, the

extent to which the parent has

childproofed the home and the level and

type of childcare that is used. Topics

covered also included bedtimes, nap

times, mealtimes, outings, and the

parents’ approach to discipline.

Parental and Child Health—The goal

of this section was to determine the

status of the parents’ health, identify

concerns about child development and

health, and assess the state of the child’s

health. This section included questions

from the Parent’s Evaluation of

Developmental Status (PEDS), by Dr.

Frances Glascoe (4). The PEDS is a tool

to identify children at risk for

developmental, behavioral, or social

delays. Therefore, it was used in this

section as a risk assessment tool to

identify children who either have or are

more likely to have problems.

Researchers interested in analyzing the

PEDS data should consult the PEDS

documentation for scoring instructions

(5). (Health care providers wishing to

use PEDS in practice to assess risk

status, or to make decisions about

developmental status for individual

children, must use the clinical version of

the test, which can be obtained from

Ellsworth & Vandermeer Press, LLC,

(4) and was not used for the NSECH.)

Financial Welfare and Health

Insurance—The goal of this section

was to determine the degree of difficulty

the household members encountered in

paying for the child’s expenses. In

addition, it detailed the level and types

of insurance available to the sampled

child. Additional topics included any

time gaps in health insurance coverage

and whether the child received benefits

from the Federal Women, Infants, and

Children program.

Demographic and Household

Information—This section provided the

following basic demographic

information:

+ The number of people in the

household

+ The race and ethnicity of the child

and the child’s mother

+ The mother’s educational level,

current employment, and marital

status.

In addition, the questions addressed the

household income, the household

location, and consistency of household

telephone service.

Computer-Assisted

Telephone Interviewing

Programming

The survey was conducted using

CATI. This data collection method

employs computer software that presents

the questionnaire on computer screens to

each interviewer. The computer program

guides the interviewer through the

questionnaire, automatically routing the

interviewer to appropriate questions

based on answers to previous questions.

Interviewers enter survey responses

directly into the computer, and the CATI

program determines whether the selected

response is within an allowable range,

checks it for consistency against other

data collected during the interview, and

saves the responses into a survey data

file. On-line help facilities are available

to aid interviewers in administering the

CATI questionnaire. This data collection

technology reduces the time required for

transferring, processing, and releasing

data.

The questionnaire was programmed

as a module of the NIS, making full use

of the CATI system’s ability to follow

skip patterns and to employ pick-lists to

present response categories. Certain

demographic questions and the question

series regarding multiple telephone lines

were identical for the NIS and NSECH

portions of the interview. These

questions were asked during the NIS

interview for NIS-eligible households

and were administered at the end of the

NSECH interview for NIS-ineligible

households.
Page 6 [ Series 1, No. 40

Once initial programming was

completed, the instrument underwent

rigorous testing to ensure correct

functioning.

Spanish Version

The questionnaire was translated

into Spanish by one translator and then

back-translated into English by another

translator. The use of two contractors

assured that each translation was done

independently of the other.

Discrepancies were resolved in

consultation with the two translators.

The Spanish version was then

incorporated into the CATI

questionnaire.

In addition, a team of experienced

Spanish-language telephone interviewers

and supervisors reviewed the Spanish

CATI instrument for accuracy and

cultural appropriateness. Issues raised by

the interview team were also resolved in

consultation with the original translators.

Pretest of Survey

Instrument

A nine-case pretest of the CATI

instrument was performed from

February 4–7, 2000, using a

convenience sample of volunteers with

children in the NSECH age range. Nine

cases with focal children of various ages

provided an initial test of the entire

instrument. The length of these

interviews ranged from 25–34 minutes.

Findings from this pretest were

incorporated into the CATI

questionnaire.

Survey Operations

Telephone interviewing began on

February 16, 2000. Data

collection was completed on July

31, 2000, with 2,068 completed

interviews, 860 of which were from the

oversample. The number of calls made

to complete an interview ranged from 1

to 99, with a mean of 7 calls and a

median of 3 calls. The respondent was

the parent or guardian who was

identified by the person answering the

telephone as primarily responsible for

the sampled child’s medical care.

Interviewing was conducted by staff

of Abt Associates Inc. under contract to

CDC and performed from Abt

Associates Inc.’s telephone centers in

Chicago, Illinois, and Las Vegas,

Nevada.

Interviewer Training

The data collection staff for the

NSECH was recruited during January

and February 2000. All of the staff had

previous NIS interviewing experience.

Full coverage of interviewing hours (9

a.m.–9 p.m. in each time zone) was

ensured. The interviewers were selected

based on their NIS experience,

interviewing skills, supervisor

evaluations, and production rates on the

NIS.

Interviewer training materials were

prepared, including a study manual,

question-by-question specifications, and

refusal aversion responses specific to

this module. Interviewer training began

on February 14, 2000. Eleven training

sessions were held for the study,

resulting in the successful training of

127 interviewers. The material covered

in the training session included an

overview of the project, introduction of

CATI screens, review of question-byquestion instructions and help screens,

and review of refusal aversion

techniques. During the course of the

training session, formal mock interviews

were completed, and interviewers

practiced administration with a partner.

The training session concluded with

evaluation of interviewers, using a mock

interview conducted with experienced

telephone center supervisors.

Advance Letter

Advance letters have been shown to

decrease nonresponse by increasing

study legitimacy (6). An advance letter

was mailed when a mailing address for

sampled telephone numbers could be

identified from residential telephone

number databases. Letters were mailed

to 49.2% of the sampled telephone

numbers. Recipients were asked to

participate in a voluntary study on the

health of young children and their

experiences with doctors. The letter

described the NIS and the NSECH,

advised recipients that their telephone

numbers had been chosen randomly, and

indicated that they might be called in

the next few weeks. (See appendix IV.)

The interview length for eligible

households was estimated at 20–25

minutes. Recipients were assured that

any information that they might give

was confidential. Toll-free telephone

numbers were provided for those who

wished to learn more about the study

and to obtain information about their

rights as study participants. The letter

was printed in English on one side and

Spanish on the other side.

Informed Consent

Consent from respondents to

participate in the survey was obtained

twice. The initial consent was obtained

after the respondents indicated that an

NIS or NSECH age-eligible child lived

in the household, but before they

provided the children’s birth dates and

other demographic information. An

additional consent procedure was

included after completion of the NIS

screening or interview (depending on

NIS age eligibility). During both

occasions, respondents were informed

about the voluntary nature of the survey,

the authorizing legislation, and

confidentiality of data collected. The

second informed-consent process

provided more information about the

content of the survey and the expected

duration. The second informed-consent

process also ensured that the person

most knowledgeable about the sample

child’s health had received the consent

information and agreed to participate;

this person may not have been the

respondent who first answered the

telephone and provided the initial

demographic information for the

children. The Institutional Review

Boards of CDC and Abt Associates Inc.

approved these procedures.
Series 1, No. 40 [ Page 7

Assurance of

Confidentiality

Participation in surveys conducted

by NCHS is voluntary, and information

collected on individuals is confidential.

For the NSECH, assurance of

confidentiality was provided to potential

respondents as part of the informed

consent procedures. In the CATI system,

interviewers acknowledged that they

read the following script to potential

respondents:

Any answers that identify you or

your family like your name or

phone number will be kept strictly

private. No one other than survey

staff can ever look at them. That’s

because this survey is being

conducted under the authority of the

Public Health Service Act. I can

provide the specific legal citation if

you want me to.

Respondents requesting the specific

legal citation were informed that:

The Public Health Service Act is

Volume 42 of the U.S. Code,

Section 242k. The collection of

information in this survey is

authorized by Section 306 of this

Act. The confidentiality of your

responses is assured by Section

308d of this Act.

Section 308d of the Public Health

Service Act (42 U.S.C. 242m) states

that:

No information, if an establishment

or person supplying the information

or described in it is identifiable,

obtained in the course of activities

undertaken or supported under

section... 306,...may be used

for any purpose other than the

purpose for which it was supplied

unless such establishment or person

has consented (as determined under

regulations of the Secretary) to its

use for such other purpose and in

the case of information obtained in

the course of health statistical or

epidemiological activities under

section... 306, such information

may not be published or released in

other form if the particular

establishment or person supplying

the information or described in it is

identifiable unless such

establishment or person has

consented (as determined under

regulations of the Secretary) to its

publication or release in other form.

Strict procedures are utilized to prevent

disclosure of confidential data in survey

operations and data dissemination.

Interview Length

The interviews averaged 35 minutes

and 36 seconds in length among

NIS-ineligible households and 32

minutes and 40 seconds (excluding the

actual NIS interview) for NIS-eligible

households. The timings differ by

NIS-eligibility because NIS-eligible

households received some demographic

and household questions during NIS

administration rather than during

NSECH. Table A shows mean and

median lengths, in minutes and seconds,

by section and NIS eligibility.

In the main sample, 48.1% (580) of

the sampled children were also

NIS-eligible. In the oversample, 52.2%

(448) of sampled children were

NIS-eligible. The average NIS interview

length is approximately 27.5 minutes.

Other Languages

From the 457 eligible households

where Spanish was spoken in the

household, 400 Spanish-language

interviews were completed (19.4%

of all completed interviews). Given the

sample size, the estimated number of

interviews that would have been

performed in any one language other

than English or Spanish was quite small.

For that reason, interviews were not

conducted in households where a

language other than English or Spanish

was spoken. A total of 183 telephone

numbers could not be resolved as

households because of a language

barrier, and 1,382 households were

identified where a language other than

English or Spanish was spoken.

The NIS uses the AT&T Language

Line to conduct interviews in languages

other than English or Spanish. Because

of confidentiality and translation

concerns, interviews for NSECH

were not conducted using the AT&T

Language Line. However, when the

AT&T Language Line was used to

determine eligibility for the NIS

interview, eligibility for the NSECH

interview could also be determined for

some households. Eligibility for the

NSECH was confirmed in 28 of these

households. An additional 1,275

households were determined to be

ineligible, whereas eligibility was not

determined in 79 households.

Toll-Free Telephone

Number

A toll-free number was provided in

the advance letter and in messages

explaining the study that were left on

answering machines. Potential

respondents could use this line to alert

the contractor that there were no

children in the study’s age range living

Table A. Average length of National Survey of Early Childhood Health interview in minutes

and seconds, by National Immunization Survey eligibility

NIS-eligible2 NIS-ineligible2

Section of NSECH1 interview Mean Median Mean Median

Overall ............................. 32:40 28:03 35:36 31:32

Screener / Introduction ................... 3:01 0:58 2:53 1:31

Section 1: Health care utilization ............. 2:53 2:31 3:01 2:46

Section 2: Parental perception of care .......... 1:48 1:38 1:50 1:38

Section 3: Interactions with healthcare providers.... 9:25 8:55 9:06 8:33

Section 4: Family interactions and home safety .... 5:25 5:07 4:54 4:38

Section 5: Parental and child health ........... 5:49 5:31 5:56 5:28

Section 6: Financial welfare and health insurance . . . 2:39 2:28 3:26 3:13

Section 7: Demographic and household

information .......................... 1:40 0:55 4:30 3:45

1NSECH is National Survey of Early Childhood Health. 2NIS is National Immunization Survey.
Page 8 [ Series 1, No. 40

or staying in their household, to ask

questions about the study, or to

complete an interview. During the

course of data collection, 1,588 calls

were received on this line, of which

82.6% were from people calling to

indicate that they did not have a child

eligible for the study. This line was used

to complete a total of 43 interviews.

Cases Pending at the Close

of Data Collection

Most of the cases pending at the

end of the field period were those in

which the number had not yet been

resolved as residential or nonresidential

(83.3% of the pending cases and 12.4%

of the total sample). A smaller number

of cases had been resolved as

households without respondent

eligibility being determined, or as

households with an eligible respondent

who did not complete the interview

(2.2% and 0.3% of the sample,

respectively).

Break-offs and Refusals

There were 126 interviews

completed with households that had

originally refused to participate (6.1% of

completed interviews). Of the cases that

were finalized as refusals, 54.5%

refused or broke off the interview

during NIS screening or interview

administration, which occurred before

the NSECH interview.

For cases that progressed past NIS

screening and interviewing, the most

common break-off point was at the

initial NSECH introduction, which

accounted for 26.3% of NSECH

refusals. This introduction to the

NSECH portion of the interview was

read to NIS-eligible and NIS-ineligible

cases, and included the second

informed-consent process. The next

most common break-off point in the

interview was at the question that

confirmed an NIS-eligible child’s age if

that child was also sampled for the

NSECH interview. This break-off point

accounted for 10.0% of refusal cases.

The item that asked for the most

knowledgeable person in the household

regarding the sampled child’s health in

order to establish the survey respondent These response rates assume that, in

was the third most common break-off the main sample, screening is complete

point, accounting for 5.6% of the as soon as it is known that there are

break-offs. Finally, an additional 3.6% NIS age-eligible or NSECH age-eligible

ended the interview at the first survey children in the household. This

question, which asked about the number assumption is critical, because it is

of times the sampled child had ever possible to calculate screening

seen a doctor or other health care completion rates for the main sample of

professional. Among the refusal cases the NSECH using two alternative

that had progressed past this first survey methods. Because of different screening

question when the respondent ended the procedures used for the main RDD

interview, there was little commonality sample and the oversample, only one

in the last question answered before method is possible for oversample cases.

ending the interview. For oversample cases, the NSECH

screener was considered to be complete

Response Rates only after all NIS-eligible children had

gone through an NIS interview and any

The interview completion rate, a NSECH-eligible children in the

measure of completed interviews among household who were not NIS-eligible

households with age-eligible children, were screened for race and ethnicity

was 79.2%. The screener completion following the NIS screener or interview.

rate, which measures the proportion of Thus, any partial NIS cases (i.e., cases

known households where a resident that were eligible for the NIS but did

reported whether or not the household not complete the entire NIS interview)

included an age-eligible child, was had not completed an NSECH screener

94.5%. The resolution rate, indicating in the oversample.

the proportion of telephone numbers that For partial NIS cases in the main

could be positively identified as either sample, the screener could be considered

residential or nonresidential, was 87.6%. complete at one of two critical points.

The Council of American Survey Because the NIS age-eligibility range is

Research Organizations (CASRO) a subset of the NSECH age-eligibility

response rate, derived from the product range, and because race/ethnicity data

of these three rates, was 65.6%. This are not needed to determine eligibility

rate is equivalent to the American for the main RDD sample, main sample

Association for Public Opinion screening could be considered complete

Research’s (7) Response Rate #3 using as soon as it was known that there were

the assumptions detailed in An NIS age-eligible children in the

alternative measure of response rate in household. This information is gathered

random-digit-dialing surveys that screen in the initial screening before any NIS

for eligible subpopulations (8). Rates interviewing. If these cases are

calculated separately for the main considered as having been screened to

sample and the oversample are be eligible at that point, all partial NIS

presented in table B. cases would be considered screened as

Table B. Response rates

Main sample Total sample, with main

screened by rostered sample screened by

Oversample dates of birth rostered dates of birth

Number of telephone lines........ 111,563 71,009 182,572

Rate

Interview completion rate ........ 82.1% 77.3% 79.2%

Screener completion rate ........ 94.4% 94.8% 94.5%

Resolution rate............... 87.2% 88.2% 87.6%

CASRO1 rate................ 67.6% 64.7% 65.6%

1CASRO is Council of American Survey Research Organizations.
Series 1, No. 40 [ Page 9

eligible for the NSECH. The response

rates reported previously are based on

screening completion rates using this

strategy.

Alternatively, screening for the

main sample could be consistent with

the screening process used for the

oversample. If this were the case, partial

NIS cases in the main sample would not

be considered as having completed an

NSECH screener. An NSECH screener

would be considered to be complete

only after the NIS interview was

complete. With this alternative strategy

for calculating screening completion

rates, the screener completion rate

decreases to 94.3%, the interview

completion rate increases to 85.2%, and

the CASRO rate increases to 70.4%.

Rates calculated separately for the main

sample and the oversample are

presented in table C.

Detailed information regarding call

outcome coding appears in appendix V.

Efforts to Maximize

Response Rates

A number of approaches were used

to maximize response rates for the

NSECH. These approaches included:

+ Careful attention to the introductory

questionnaire script to ensure that it

engaged the interest of potential

respondents and provided clear

information regarding the study

sponsor

+ Thorough pretesting of the survey

instrument to ensure that it was

clear to respondents and did not

place an undue burden on them

Table C. Alternative response rates

+

+

+

+

+

+

An advance mailing to households

having directory-listed telephone

numbers to lay the groundwork for

obtaining cooperation on first

contact

A toll-free telephone number to

allow respondents to contact Abt

Associates Inc. staff, encouraging

potential respondents to obtain

information about the study,

immediately establish study

eligibility, and voice any concerns

A Spanish-language version of the

survey instrument to reduce

nonresponse bias in Spanishspeaking households

A sample management plan that

ensured that the correct number of

cases were in the field at any given

time, and provided daily review of

appointment and refusal case status

to ensure timely recontact

An interviewer training program in

refusal aversion to reduce the

number of unresolved cases and

refusals to participate

Refusal conversion attempts by

specially trained interviewers who

prepared case-specific strategies for

each conversion call based on call

history

Data Files

ASAS (v6) data file containing all

completed interviews (n =

2,068) was created. This file

contains one record per sample child,

with all information about the household

on that record.

Editing

Concurrent with the development of

the CATI questionnaire for the NSECH

data collection phase, a detailed plan for

checking and editing the data in the

CATI instrument was developed. The

intention was to design into the CATI

software consistency checks across data

elements, valid range codes, and a

method to identify incorrect codes

entered by interviewers. To the extent

that the CATI software could be

developed to perform these tasks, the

efficiency of postsurvey data cleaning

and processing was increased.

The CATI system was designed to

perform a number of edits as an

interviewer enters data into the

computer system. These edits dealt with

errors that could be reconciled while the

respondent was on the telephone and

focused, in particular, on items critical

to the conduct of the study. The CATI

edit specifications were designed to

correct respondent error during the

interview (for example, a respondent

saying two children under 3 years of

age lived in the household, but only

listing one name on the roster) and to

identify and correct data-entry error by

interviewers (for example, a 9-month

old child is reported as being introduced

to solid foods when she was 4 months

old, but the interviewer attempts to enter

14 months). To the extent possible

without making the CATI system overly

complicated, out-of-range and

inconsistent responses resulted in a

warning screen for the benefit of the

interviewer, who was trained to correct

errors as they occurred. These messages

were designed primarily to prevent data

entry errors and respondent errors and

not to challenge respondents who gave

logically inconsistent responses.

Total sample, with main

Main sample screened sample screened on

upon completion of NIS completion of NIS

Oversample screener/interview1 screener/interview1

Number of telephone lines........ 111,563 71,009 182,572

Rate

Interview completion rate ........ 82.1% 87.5% 85.2%

Screener completion rate ........ 94.4% 94.1% 94.3%

Resolution rate............... 87.2% 88.2% 87.6%

CASRO2 rate................ 67.6% 72.7% 70.4%

1NIS is National Immunization Survey. 2CASRO is Council of American Survey Research Organizations.

The two main types of CATI edits

were range checks and consistency

checks. A range violation would result

in visual notification to the CATI

interviewer (a pop-up box). In most

cases the interviewer would have to

enter a valid response to continue the

interview (such situations constitute

‘‘hard edits’’). However, some

out-of-range responses would produce a

warning, and the interviewer would be

instructed to verify the answer provided
Page 10 [ Series 1, No. 40

by the respondent. If the respondent

confirmed the out-of-range value, the

interviewer was allowed to continue

(these were ‘‘soft edits’’). A consistency

violation would also result in a pop-up

box indicating that an inconsistency

between two responses had been

detected. The interviewer would then

have the opportunity to change one or

both of the values entered. In some

cases the interviewer had the option to

proceed if the respondent confirmed the

inconsistent values. There are trade-offs

between, on the one hand, incorporating

every possible type of error check into a

CATI system and, on the other hand,

overall performance of the CATI system

and the use of development resources.

To reconcile this trade-off, post-CATI

edits were developed to resolve

problems that did not require access to

the respondent. Any problems that could

not be resolved without further access to

the respondent were left inconsistent.

After the preprogrammed edits were

run, frequency distributions of all the

variables in the file were produced and

reviewed. Each variable’s range of

permissible values was examined for

any additional invalid values or unusual

distributions. Invalid values, where they

occurred, were blanked out. If blank

values already existed for a variable,

they were checked to determine whether

they were allowable, due to legitimate

skips, or occurred in excessive numbers.

When blank values were the result of

skip patterns, a ‘‘legitimate skip’’ code

was used. Other records that were

missing responses for unknown reasons

were left missing. When necessary for

later calculating sampling weights, some

missing values were imputed (see

‘‘Imputation’’ section).

One variable (A7Q12_A) was

dropped from the data set because of the

unreliability of the data collected. The

question asked about the number of

times the child moved since he/she was

born and was asked only if the

respondent indicated that the child’s

mother did not live at the same address

as she did when the child was born.

Using information about the mother’s

mobility as the basis for asking about

the child’s mobility was inappropriate as

several respondents reported that the

mother had moved but the child had

not. Therefore, data from this question

were suppressed.

Imputation

Because race, ethnicity, and

mother’s education were used in the

sampling weights, these variables were

imputed for children for whom such

information was missing. Imputation

was conducted using a hot-deck

procedure; that is, the data for these

variables were borrowed from another

record that closely matched the record

for which these variables were missing.

The variable KFLG_RAC indicates

which cases have an imputed race for

the child, KFLG_HIS indicates which

cases have an imputed ethnicity for the

child, and KFLG_EDU indicates which

cases have an imputed education for the

mother.

Edits to Protect

Confidentiality

NCHS takes extraordinary measures

to assure that the identity of data

subjects cannot be disclosed. The risk of

inadvertent disclosure of confidential

information about individual respondents

is higher with a publicly released data

set having both detailed geography

variables and a detailed and extensive

set of other survey observations.

Coarsening a data set by suppressing

survey variables, collapsing multiple

variables into one, collapsing response

categories for other variables, and/or

introduction of noise in the data are

common techniques to reduce the risk of

inadvertent disclosure.

In this data set, the child’s date of

birth has been suppressed, but the

child’s age (in months) at the time of

the interview has been reported.

Geographic information that would

identify the specific IAP area in the

United States has been dropped from the

data set. It has been replaced with a

four-category variable representing U.S.

Census Bureau regions. The responses

for the race variable have been reduced

to five categories (white, African

American or black, Asian, Native

American or Alaska Native, and other).

Hispanic origin (yes or no) has been

reported separately from race, but

specific Hispanic origin (e.g., Mexican)

has been suppressed. Education level for

the child’s mother has been recoded to

three categories (less than high school,

high school graduate, and more than

high school). Family income has been

reported as eight categories (less than

$7,500, $7,501–$17,500, $17,501–

$25,000, $25,001–$35,000, $35,001–

$45,000, $45,001–$60,000, $60,001–

$75,000, and $75,001 and over).

The child’s weight at birth was

recoded into grams (if reported as

pounds and ounces) and then reduced to

seven categories (less than 1,500,

1,500–2,499, 2,500–2,999, 3,000–3,499,

3,500–3,999, 4,000–4,499, and 4,500

and over). For mothers who breastfed

for less than 1 month, the duration of

breastfeeding is reported in days. The

duration for mothers who breastfed for

more than 1 month was recoded into

months, with a top code of 12 months

or longer. In addition, many other

frequency variables have been topcoded

to suppress outliers at the high end of

the distribution of responses. Because of

their unusual characteristics, these

outliers might have been more readily

identifiable. Therefore, the following

variables have been topcoded:

+ For number of doctor visits for any

reason in past year, 16 visits or

more is the maximum reported.

+ For number of well-child visits in

past year, 11 well-child visits or

more is the maximum reported.

+ For number of hours child spends in

childcare, 60 hours or more is the

maximum reported.

+ For number of visits to the

emergency room in past year, seven

visits or more is the maximum

reported.

+ For number of overnight hospital

stays in past year, seven stays or

more is the maximum reported.

+ For number of telephone calls to a

doctor in past year, 50 calls or more

is the maximum reported.

Some demographic variables have

also been topcoded to suppress outliers

at the high end of the distribution of

responses. The maximum number of

children under 18 years of age reported

as living in the household has been

limited to four or more; the maximum
Series 1, No. 40 [ Page 11

number of adults reported as living in

the household has been limited to six or

more; and the total number of persons

in the household has been suppressed.

Finally, the exact age (in years) of the

child’s mother has been restricted to

18–48 years of age, with codes for ages

17 or under and 49 or over.

Additional Edits

+ A1Q02R was created from A2Q02

and A1Q02_A.

+ A1Q04R was created from A1Q04,

A1Q05, and A1Q05_A. For

example, when respondents

indicated a place rather than a

provider in A1Q05_A, A1Q04 was

recoded to ‘‘no.’’

+ A1Q05R to A1Q10_AR and

A1Q10BZ1 to A1Q10BZ4 were

created as a result of the edit that

created A1Q04R. For all records

where respondents indicated a place

rather than a provider in A1Q05_A,

these follow-up questions were

coded to ‘‘legitimate skip.’’

+ In addition, A1Q05R was further

edited based on A1Q05 and

A1Q05_A. For example, when

respondents indicated a kind of

provider in A1Q05_A that could be

coded as one of the A1Q05 options,

we changed the response in A1Q05

from ‘‘other’’ to that option.

+ A7Q01_AR was created from

A7Q01_A.

+ A7Q08R was created from A7Q08

and A7Q08_A.

+ A7Q11R was created from A7Q11

and A7Q11_A.

+ BASE9 is an indicator of how many

respondents reported either the child

not getting needed care or the child

getting delayed care. This variable

serves as the denominator for

estimates derived from A5Q09_C.

+ BFEEDR was created from A3Q54,

A3Q54_A, and A3Q54_B.

+ EDUCMOM was created from

A7Q06.

+ I_HISP_K was created from A7Q02.

+ I_RACEKR was created from

A7Q03 and A7Q04.

+ IND_OTH was created from A6Q07

and A6Q08.

+ INSURE was derived from

responses to questions A6Q02

through A6Q09_A. Any child with

insurance coverage reported in

questions A6Q02 through A6Q08, or

in A6Q09_A, is considered insured.

+ MED_SCHP was created from

A6Q02 and A6Q04.

+ MOMHISP was created from

A7Q09.

+ MOMRACER was created from

A7Q10 and A7Q10_A.

+ NUMCHILR was created from

A7Q01 and A7Q01_A.

+ XBESTINC was created from

variables A7Q13 to A7Q26.

Dummy Variables

When respondents were permitted

to provide multiple answers for the

same question, a variable was created

for each possible answer. The values for

these new dummy variables are ‘‘yes,

this answer was given’’ and ‘‘no, this

answer was not given.’’ When

respondents could not or did not provide

an answer to the question, a value of

‘‘don’t know’’ or ‘‘refused’’ is reported

for each of the dummy variables.

+ A1Q10B is represented by

A1Q10BZ1 to A1Q10BZ4.

+ A2Q04 is represented by A2Q05X01

to A2Q04X06.

+ A3Q47_A is represented by

A3Q47A01 to A3Q47A07.

+ A3Q48_A is represented by

A3Q48A01 to A3Q48A04.

+ A5Q09_C is represented by

A5Q09CX1 to A5Q09CX4.

When questions were repeated

because they referred to different

subjects, it was necessary to distinguish

the referenced subjects in the data file.

Questions A5Q09_D and A5Q09_E

could be repeated for each of four

different types of problems or concerns

(A5Q09_C).

+ A5Q09_D_X01 is represented by

A5Q09D11 to A5Q09D14.

A5Q09D11 refers to a medical

problem or concern (A5Q09_C = 1),

A5Q09D12 refers to a behavioral

problem or concern (A5Q09_C = 2),

A5Q09D13 refers to a speech

problem or concern (A5Q09_C = 3),

and so on.

+ A5Q09_D_X02 is represented by

A5Q09D21 to A5Q09D24.

+ A5Q09_D_X03 is represented by

A5Q09D31 to A5Q09D34.

+ A5Q09_D_X04 is represented by

A5Q09D41 to A5Q09D44.

+ A5Q09_D_X05 is represented by

A5Q09D51 to A5Q09D54.

+ A5Q09_E_X01 is represented by

A5Q09E11 to A5Q09E14.

+ A5Q09_E_X02 is represented by

A5Q09E21 to A5Q09E24.

+ A5Q09_E_X03 is represented by

A5Q09E31 to A5Q09E34.

Estimation Procedures

The NSECH took its sample cases

from another survey, the NIS.

The NIS is designed to collect an

equal number of completed interviews

from 78 different areas (the 50 States,

the District of Columbia, and an

additional 27 localities of interest to

policymakers). The NIS collects data

quarterly. There is enough sample each

quarter to obtain between 101 and 129

completed NIS interviews in each of the

78 areas. To reach this number of

completed interviews, the total number

of telephone lines randomly generated

and screened for eligibility in each area

ranges, for example, from 3,547 to

15,863 (Q1/2000). To manage this large

sample, these lines are randomly divided

into smaller groups called sample

replicates.

Base Sampling Weight

The goal of the NSECH was to

complete at least 2,000 interviews. First,

the total number of telephone lines

required to obtain this number of

completes was estimated. Staff then

selected enough sample replicates from

the NIS sample to obtain the requisite

number of completes for the NSECH.

Thus, the telephone lines selected to

be screened for the NSECH was a

random sample of the lines selected to

be screened for the NIS, which in turn

was a random sample of all possible

telephone lines in each geographic area.

The probability that any given telephone

line will be selected from the population

of all possible telephone lines can be

calculated:
Page 12 [ Series 1, No. 40

If there were 1,000 total telephone

lines in a given area, and 100 of

those lines were selected for the

study, the probability that any single

telephone line would be selected is

100/1000, or .10.

Each telephone line selected for the

NSECH represents some larger number

of telephone lines in the geographic

area. This number can be calculated as

the inverse of the probability of

selection for any single telephone line:

If the probability of selection for

any single telephone line was .10,

each telephone line selected

represents 1/.10, or 10, telephone

lines in the geographic area.

This number—the inverse of the

probability of selection for any single

telephone line—is the base sampling

weight and was associated with each

completed interview in that geographic

area. The base sampling weights vary by

geographic area, but were the same for

every completed interview from that

geographic area. Because the population

of telephone numbers did not change

much by quarter, the base sampling

weight was calculated for the overall

survey and not separately for each

quarter.

Households with Multiple

Telephone Lines

If a household has multiple

voice-use telephone lines, this household

has a greater chance of being included

in the survey than does a household

with only a single voice-use telephone

line. Because the NSECH is a survey of

households and of children in those

households, each household should have

an equal probability of being in the

sample. To adjust for the increased

probability of multiple telephone

households being included in the

sample, the base sampling weight is

divided by the number of voice-use

telephone lines in the household:

If a household had two voice-use

telephone lines, this household

could be included in the sample 2

times. If it were included twice, the

household would represent, say, 10

(base sampling weight) x 2 (number

of telephone lines) = 20 households.

To adjust the weight so that the

multiple-telephone household in the

sample represents the same number

of households in the geographic

area as does a single-line

household in the sample, the base

sampling weight (10) is divided by

the number of telephone lines (2).

With an adjusted weight of 5, this

household (had it been selected

twice) would still represent only 10

households (5x2= 10).

The First Form of

Nonresponse: Unknown

Household Status

When the selected telephone lines

are called, three results are possible:

+ It is determined that the telephone

line belongs to a household.

+ It is determined that the telephone

line is not a working residential

number, but rather is a business

number or is nonworking.

+ The status is undetermined because

the telephone rings without an

answer, the person answering the

telephone hangs up immediately, or

the telephone answering device does

not indicate whether the telephone

line belongs to a household.

This third category includes some

household telephone lines. The exact

number of household telephone lines in

this category is unknown. Still, the

completed household interviews must

represent the households in this

‘‘unknown’’ category. When the number

of households in the unknown category

is large, the weight for each completed

household interview must be increased a

great deal. When the number of

households in the unknown category is

small, the weight for each completed

household interview must be increased

only a little bit. This proportional

adjustment is the first unit nonresponse

adjustment.

The size of the adjustment is based

on the size of the ‘‘unknown’’ category

after all numbers have been called

several times, and is based on previous

research in which telephone company

business offices reported on the number

of households among the ‘‘unknown’’

numbers. This adjustment varies based

on geographic area, telephone area code,

and whether the telephone line was

directory-listed. When many telephone

numbers in a geographic area and area

code go unanswered, and most of these

numbers are highly likely to be

households, the weights for completed

interviews in that geographic area and

area code are increased greatly. When

few telephone numbers in a geographic

area and area code go unanswered, or

few of these numbers are likely to be

households, the weights for completed

interviews in that geographic area and

area code are increased only slightly.

In other words, based on the

frequency of the nonresponse in a given

area, compensation is made for this

nonresponse by proportionately

increasing the weights for those

interviews that could be completed in

that area. The completed interviews,

therefore, represent the households in

the ‘‘unknown’’ category.

Separation of the

Telephone Lines Into the

Main Sample and the

Oversample

After the telephone lines were

selected, they were divided into two

samples, including a general sample to

collect data on all children 4–35 months

of age (the ‘‘main sample’’); and a

sample that was to collect data only

from households that had a black

non-Hispanic or Hispanic child 4–35

months of age (the ‘‘oversample’’).

The total number of telephone lines

needed to obtain a certain number of

completes in the main sample was

approximated by reviewing the

proportion of children 19–35 months of

age historically observed in the NIS

(this is the age range targeted by the

NIS). The number of telephone lines

selected for the main sample in each of

the 78 areas was proportional to the

number of children we expected to find

in that area.

The number of telephone lines

needed for the oversample was

estimated in the same fashion, except
Series 1, No. 40 [ Page 13

that we also took into consideration the

proportion of the population that is

black non-Hispanic or Hispanic to guide

how the expected total number of

completes should spread across the 78

geographic areas. The number of

telephone lines selected for the

oversample in each of the 78 areas was

proportional to the number of black

non-Hispanic or Hispanic children we

expected to find in that area. This way,

the number of telephone lines selected

in localities with low proportions of

black non-Hispanics and Hispanics was

minimized.

Operationally, certain NSECH

sample telephone numbers were flagged

as being part of the main sample and

some as part of the oversample. If a

telephone number was flagged as part of

the main sample, the household was

screened for any child between 4–35

months old. If the telephone number

was flagged as part of the oversample,

the household was further screened for a

black non-Hispanic or Hispanic child

within the age range. Therefore, in the

main sample, all households with

children of this age were asked to

complete the survey, as opposed to the

oversample telephone numbers, which

were asked to complete an interview

only if there was a black non-Hispanic

or Hispanic child between 4–35 months

old.

The Second Form of

Nonresponse: Unknown

Household Eligibility

When a household has been

identified, three results are possible:

+ It is determined that the household

includes an eligible child;

+ It is determined that the household

does not include an eligible child; or

+ The screening interview is not

completed, and the eligibility of the

household is unknown.

This third category includes some

eligible households. The exact number

of eligible households in this category is

unknown. Still, the completed household

interviews must represent the eligible

households in this ‘‘unknown’’ category.

When the number of eligible households

in the unknown category is large, the

weight for each completed household

interview must be increased a great deal.

When the number of eligible households

in the unknown category is small, the

weight for each completed household

interview must be increased only a little

bit. This proportional adjustment is the

second unit nonresponse adjustment.

The size of the adjustment is based

on the size of the first two categories.

That is, the proportion of eligible

households in the unknown category is

assumed to be the same as the

proportion of eligible households among

all households where the screening

interview was completed. This

adjustment varies based on geographic

area. Additionally, because the eligibility

criteria are different for a main sample

household than for an oversample

household, the adjustment varies by

sample type. When the eligibility for

many households in a geographic area

and particular sample is unknown, and a

high proportion of the completed

eligibility interviews in that area

revealed eligible children, the weights

for completed interviews in that

geographic area and sample are

increased greatly. When the eligibility

for only a few households in a

geographic area and sample is unknown,

or few of the completed eligibility

interviews in that area revealed eligible

children, the weights for completed

interviews in that geographic area and

sample are increased only slightly.

In other words, based on the

frequency of nonresponse to the

screening interview in a given area and

in a given sample, compensation is

made for this nonresponse by

proportionately increasing the weights

for those interviews that could be

completed in that area and within that

sample. The completed interviews,

therefore, represent the eligible

households in the ‘‘unknown’’ category.

Adjustment for

Subsampling in the

Oversample

Because telephone numbers were

not selected independently for the

national sample and the oversample, an

adjustment compensates for the

exclusion of age-eligible nonminority

children from the oversample. This

adjustment increases the weight for

nonminority children in the main sample

so that they also represent the

nonminority children we did not

interview in the oversample. This

adjustment is the subsampling

adjustment.

The Third Form of

Nonresponse: Eligible

Households Who Do Not

Complete the Interview

When an eligible household has

been identified, two results are possible:

+ An interview is completed

+ An interview is not completed

To be considered a completed interview,

the interviewer must have asked all

questions for which the household was

eligible, up to and including the Parental

and Child Health section (i.e., through

question A5Q12). Completed interviews

may include item nonresponse.

The completed household interviews

from the first category must represent

the eligible households in the

‘‘incomplete’’ second category. When

the number of incomplete interviews is

large, the weight for each completed

household interview must be increased a

great deal. When the number of

incomplete interviews is small, the

weight for each completed household

interview must be increased only a little

bit. This proportional adjustment is the

third unit nonresponse adjustment.

The size of the adjustment is based

on the size of the two categories, and is

calculated simply as the ratio of the

total number of eligible households to

the number of completed interviews.

This adjustment varies based on

geographic area and sample type (main

sample or oversample).

In other words, based on the

frequency of nonresponse among

eligible households in a given area and

in a given sample, compensation is

made for this nonresponse by

proportionately increasing the weights

for those interviews that could be
Page 14 [ Series 1, No. 40

completed in that area and within that

sample. The completed interviews,

therefore, represent the eligible

households with incomplete interviews.

The Child-Level Weight

In the main sample, one child 4–35

months of age was randomly selected

from among all of the children within

that age range. In the oversample, one

black non-Hispanic or Hispanic child

4–35 months of age was randomly

selected from among all of the black

non-Hispanic or Hispanic children

within that age range. In households

with multiple eligible children, the

randomly selected child represents all of

the nonselected children in the

household. Therefore, the sampling

weight for this completed interview

must be increased to reflect the fact that

this completed interview ‘‘represents’’

multiple children in that household.

This adjustment simply multiplies

the household weight (as adjusted for

multiple telephone lines and by all three

nonresponse factors) by the number of

eligible children in the household. For

completed interviews in the main

sample, the multiplier was the number

of children 4–35 months of age. For

completed interviews in the oversample,

the multiplier was the number of black

non-Hispanic and Hispanic children in

the household 4–35 months of age.

Poststratification

Despite the weighting efforts and

the nonresponse adjustments, the

estimated proportion of children by race,

sex, and age are unlikely to perfectly

match the population sampled. Any

discrepancies are likely to be due to

random sampling error and nonrandom

response biases. Among these biases

may be increased nonresponse based on

race, sex, age, or mother’s education.

The previous nonresponse adjustments

used completed interviews to adjust for

incomplete interviews, and therefore

assume that the children in households

with completed interviews are similar to

children in households with incomplete

interviews (within the bounds of

geographic areas, area codes, sample

types, and willingness to list the

telephone number in the directory).

Poststratification adjusts the weights to

match population control totals for key

demographics (race, sex, age, and

mother’s education) obtained from an

independent source.

For the NSECH, the independent

source was the National Vital Statistics

System counts of children born in the

United States between May and

December of 1997 and all months of

1998 and 1999. This range of birth

months is 4–35 months before the

midpoint of the NSECH data collection,

April 2000. Adjusting the weights based

on these population control totals for

age, sex, race, and mother’s education

helps compensate for any potential

response biases within these groups.

These counts were adjusted for

infant mortality and immigration. The

adjustments to the vital statistics data

are the same ones used by the NIS to

poststratify the NIS weights (see chapter

8 of the 1994 NIS Methodology Report

(9)). These adjustments are necessary

because the use of the raw (unadjusted)

natality data file to form the required

population control totals for the NIS has

two significant limitations.

First, the natality file will not

reflect children born outside the United

States who immigrate to this country

before reaching 19–35 months of age.

This immigration will increase the

population size of children, but the

effect is likely to vary considerably

from IAP area to IAP area. For the NIS,

the Public Use Microdata Samples

(PUMS) from the 1990 Census are used

to estimate by race group the number of

2-year-olds in each State who were

born outside the United States.

Second, the natality file provides a

universe of live births, and therefore it

does not reflect infant mortality. To

adjust for this reduction in the

population, 1989 State-specific infant

mortality rates (deaths under 1 year) by

race group (white versus nonwhite) were

applied to the vital statistics data. Of

course, these rates do not relate directly

to the 1997–99 birth cohort, but were

used because they relate directly to the

1990 Census data used for the

immigration adjustment. It should be

noted that mortality in the second and

third years of life has not been taken

into account. However, this mortality is

unlikely to have much impact on the

population control totals.

In total, the immigration and infant

mortality adjustments have a small

impact on the vital statistics control

totals as shown in table D.

The poststratification adjustment

also adjusts for the potential bias that

may exist because the NSECH, as a

telephone survey, could not select

households without a telephone at the

time of the survey. To make this

adjustment, the poststratification control

totals from the vital statistics were split:

One control total for households with

telephones and one control total for

households without telephones or with

an interruption in telephone service for

at least 1 week during the past 12

months. The proportion allocated to

each group was based on 2000 Current

Population Survey data for households

without telephones and NSECH data for

households with interrupted telephone

service. The relative size of the race,

age, sex, and education categories were

the same within each telephone service

group.

There is evidence to suggest that

households with telephones at the time

of the survey, but with interruptions in

telephone service during the year, are

more similar to households with no

telephone service at the time of the

survey than households with

uninterrupted telephone service during

the year (10, 11, and 12). Therefore,

Table D. Unadjusted and adjusted vital statistics control totals

Unadjusted Adjusted Percent

control total control total difference

Total ..................... 10,537,670 10,726,319 1.8

Racial group

White..................... 8,338,886 8,423,726 1.0

Nonwhite .................. 2,198,784 2,302,593 4.7
Series 1, No. 40 [ Page 15

some compensation for nonresponse by

nontelephone households can be made

by proportionately increasing the

weights for those interviews that could

be completed in households with

interrupted service. In this way,

completed interviews in households with

interrupted service represent the

incomplete interviews in households

without telephone service at the time of

the interview.

Household size was considered for

poststratification control totals of the

NSECH household weights. However,

we were unable to locate stable control

totals for household size at the time of

the survey.

Interpretation of Weighted

Estimates

Data users are urged to use caution

when interpreting estimates based on the

sampling weights. Estimates based on

the sampling weights generalize only to

the U.S. population of children 4–35

months of age. These estimates do not

generalize to the population of parents,

the population of mothers, or the

population of children’s health care

providers.

Variance Estimation and

Hypothesis Testing

The NSECH data were obtained

through a complex sample design

involving clustering and stratification.

Because of the complex design, the

direct application of standard statistical

analysis methods for variance estimation

and hypothesis testing may yield

misleading results.

There are computer programs

available that provide the capability of

variance estimation for complex sample

designs. For example, SUDAAN is one

program that calculates the variancecovariance matrix using the linearization

approach (Taylor series expansion). To

provide the user with the capability of

estimating the complex sample variances

in the SLAITS data, we have provided

stratum identifiers and primary sampling

unit (PSU) codes on the data files. (The

PSU for the NSECH is the household.)

These variables and the sample weights

are necessary for the calculation of

variances.

It should be noted that the stratum

identifiers reported on the data set are

not specific to IAP areas. Independent

samples were selected from each IAP

area in proportion to the total number of

households with young children and the

total number of households with young

black non-Hispanic or Hispanic children

in each IAP area. Therefore, these IAP

areas should be considered strata for

variance estimation. However, disclosure

of the specific IAP area for each child

(even if the code is scrambled) could

increase the risk of disclosure of a

respondent’s identity. For example, the

IAP area with the highest frequency of

responses in the West region would be

readily identifiable as California.

Therefore, the 78 IAP areas have been

collapsed into 18 strata by

systematically combining 3–6 IAP areas

into each stratum. At no point were IAP

areas in one census region collapsed

with IAP areas in another census region,

so regional estimates will be possible.

But all strata now contain data from at

least three States, which limits the risk

of disclosure. However, in some cases,

limited reporting of strata can affect

statistical inferences drawn from the

data. The IAP areas were combined in a

systematic fashion developed to

minimize the impact on variance

calculations. The standard errors for

national estimates with key variables

were affected only slightly and not in a

consistent direction. The Office of

Research and Methodology at NCHS

has confirmed that the restricted strata

identifiers do not have a considerable

impact on variance calculations or

statistical inferences.

The overall number of persons in

this survey is sufficient for most

statistical inference purposes. However,

analyses of some rare responses and

analyses of subclasses can lead to

estimators that are unreliable.

Consequently, these analyses require that

the user pay particular attention to the

coefficient of variation for the estimates

of means, proportions, and totals. In

addition, small sample sizes or a small

number of strata used in the variance

calculations may produce unstable

estimates of the variances using the

aforementioned computer programs.

Variance Estimation Using

SUDAAN

This method requires no recoding of

design variables and may be applicable

to many complex survey sample design

computer programs, but is statistically

less efficient (and therefore more

conservative) than some other methods

because the PSU unit is treated as being

sampled with replacement within the

stratum unit. The data file needs to

sorted only by stratum and PSU (i.e.,

household identifier) before invoking

SUDAAN. The following SUDAAN

design statements are used:

PROC... DESIGN = WR;

NEST STRATUM PSU;

WEIGHT FINALRKW;

Variance Estimation Using

STATA

The following STATA design

statements are used:

svyset strata STRATUM

svyset psu PSU

svyset pweight FINALRKW

svyset

Quality Control

To ensure high quality data,

program staff continually

monitored the interviewers, the

sample selection procedures, the

consistency of the data, and the

estimation procedures.

Quality Control of

Interviewing

Telephone center supervisors were

available to interviewing staff at all

times to resolve any questions or

concerns about a case. Supervisors

regularly observed the interviewing floor

to informally monitor interviewers. In

addition, supervisory staff used remote
Page 16 [ Series 1, No. 40

telephone and computer monitoring

technology to ensure that all

interviewers performed according to

project specifications. This formal

monitoring was conducted to ensure that

introductory material was properly read,

that item wording and sequence of the

questionnaire were followed correctly,

that respondent questions were answered

properly, and that any vague responses

were properly probed. Computer

monitoring also allowed supervisors to

ensure that answers were entered into

the CATI system accurately.

Selection of interviewers for

monitoring was automated using an

algorithm that ensured that newly

trained interviewers were monitored

more often than experienced

interviewers. Experienced interviewers

were prioritized for monitoring based

upon the length of time since their last

monitoring session and recent

monitoring scores. Each interviewer was

typically monitored at least once a

week; however, some interviewers were

monitored more often depending on the

rules of prioritization. Supervisory staff

monitored 5% of all calls made for the

NSECH.

Sample Monitoring and

Quality Control

The prepared sample of telephone

numbers was checked to ensure that it

met the sample design specifications.

The sample was monitored daily to

ensure that the pace of data collection

was consistent across the data collection

period and to prevent the unnecessary

release to CATI of excess cases. Daily

analyses of the dynamics in the CATI

sample were produced to assist in timely

sample management decision-making.

Data Quality Control

The CATI system was programmed

to help ensure complete and accurate

data collection, using automated data

checking techniques, such as responsevalue range checks and consistency

edits, during the interview process.

These features enabled interviewers to

obtain needed clarifications while still

on the telephone with the respondent.

Throughout data collection, interview

data were reviewed for consistency

between fields, appropriate responsevalue ranges, skip logic patterns, and

missing information.

Estimation Quality Control

Formulas developed by the

sampling statistician for the weights and

adjustments were compared with the

actual weights and adjustments

constructed by the statistical

programmer. The variables delivered by

the data collection staff to the statistical

programmer were used to create

independent calculations of the weights

to check the programmer’s

implementation of the statistician’s

weighting specifications.

In addition to this independent

check, univariate statistics were

produced and reviewed for the

adjustments and weights. Reviewers

used general knowledge about the size

of the population and expectations for

IAP area behavior. For example,

interview cooperation rates are typically

lower in certain IAP areas (e.g., urban

centers) than others (e.g., States in the

South and Midwest); the NSECH

weights reflect this difference. In

addition, the sums of the various

weights were compared to ensure that

the differences were in the expected

direction (e.g., the sum of the child

weights is larger than the sum of the

household weights).

Guidelines for

Data Use

With the goal of mutual benefit,

NCHS requests that recipients

of data files cooperate in

certain actions related to their use.

Any published material derived

from the data should acknowledge

NCHS as the original source. The

suggested citation, ‘‘Data Source:

Centers for Disease Control and

Prevention, National Center for Health

Statistics, State and Local Area

Integrated Telephone Survey, National

Survey of Early Childhood Health,

2000,’’ should appear at the bottom of

all tables. It should also include a

disclaimer that credits any analyses,

interpretations, or conclusions reached to

the author (recipient of the file) and not

to NCHS, which is responsible only for

the initial data. Consumers who wish to

publish a technical description of the

data should make a reasonable effort to

ensure that the description is not

inconsistent with that published by

NCHS.

The Public Health Service Act

(Section 308d) provides that data

collected by NCHS may be used only

for the purpose of health statistical

reporting and analysis. Any effort to

determine the identity of any reported

case is prohibited by this law. NCHS

takes extraordinary measures to ensure

that the identity of data subjects cannot

be disclosed. All direct identifiers, as

well as any characteristics that might

lead to identification, are omitted from

the data set. Any intentional

identification or disclosure of a person

or establishment violates the assurances

of confidentiality given to the providers

of the information. Therefore, users

must:

+ Use the data in this data set for

statistical reporting and analysis

only

+ Make no use of the identity of any

person or establishment discovered

inadvertently or otherwise, and

advise the Director, NCHS, of any

such discovery

+ Not link this data set with

individually identifiable data from

any other NCHS or non-NCHS data

sets

Use of the data set signifies users’

agreement to comply with the

aforementioned stated statutory-based

requirements.

References

1. Zell ER, Ezzati-Rice TM, Battaglia MP,

Wright RA. National immunization

survey: The methodology of a

vaccination surveillance system. Public

Health Reports 115:65–77. 2000.

2. Bethell C, Peck C, Schor E. Assessing

health system provision of well-child
Series 1, No. 40 [ Page 17

care: The promoting healthy

development survey. Pediatrics

107:1084–93. 2001.

3. Abt Associates Inc. The National

Immunization Survey (NIS): 1999

annual methodology report. Cambridge,

MA: Abt Associates Inc. In preparation.

4. Glascoe FP. Parents’ evaluation of

developmental status: a method for

detecting and addressing developmental

and behavioral problems in children.

Nashville, TN: Ellsworth &

Vandermeer Press, LLC. 1997.

5. Glascoe FP. Collaborating with parents:

using parent’s evaluation of

developmental status to detect and

address developmental and behavioral

problems. Nashville, TN: Ellsworth &

Vandermeer Press, LLC. 1998.

6. Camburn DP, Lavrakas PJ, Battaglia

MP, et al. Using advance respondent

letters in random-digit dialing telephone

surveys. Presentation for American

Association for Public Opinion

Research Conference. May 1995.

7. American Association for Public

Opinion Research. Standard definitions:

Final dispositions of case codes and

outcome rates for surveys. Ann Arbor,

MI: Author. 2000.

8. Ezzati-Rice TM, Frankel MR, et al. An

alternative measure of response rate in

random-digit-dialing surveys that screen

for eligible subpopulations. Journal of

Economic and Social Measurement

26:99–109. 2000.

9. Abt Associates Inc. The National

Immunization Survey (NIS): 1994

annual methodology report. Chicago:

Abt Associates Inc., 1995.

10. Brick MJ, Waksburg J, Starer A. Bias

in list-assisted telephone samples.

Public Opinion Quarterly 59:218–235.

1995.

11. Frankel MR, Srinath KP, Battaglia MP,

et al. Using data on interruptions in

telephone service to reduce

nontelephone bias in a random-digitdialing survey. In Proceedings of the

Section on Survey Research Methods.

Alexandria VA: American Statistical

Association. In press.

12. Keeter S. Estimating telephone

noncoverage bias with a telephone

survey. Public Opinion Quarterly

59:196–217. 1995.

13. Srinath, KP. Allocation to strata when

sample selection is through screening a

larger sample. In Proceedings of the

Section on Survey Research Methods

1999. Alexandria, VA: American

Statistical Association. 351–4. 1999.

14. Shapiro G, Battaglia M, Camburn D, et

al. Calling local telephone company

business offices to determine the

residential status of a wide class of

unresolved telephone numbers in a

random-digit-dialing sample. In

Proceedings of the Section on Survey

Research Methods. Alexandria, VA:

American Statistical Association.

975–80. 1995.

15. Brick JM, Waksberg J, Keeter S. Using

data on interruptions in telephone

service as coverage adjustments.

Survey Methodology 22 (2). 185–97.

1996.
Page 18 [ Series 1, No. 40

Appendix I

Sampling and Sampling

Weights Technical

Summary

Sampling Design

The objective for the State and

Local Area Integrated Telephone Survey

(SLAITS) National Survey of Early

Childhood Health (NSECH) was to

select a national sample of 1,200

children between 4–35 months of age

and an additional sample of 800 black

non-Hispanic or Hispanic children in the

same age group. The main sample of

1,200 children included children from

all racial and ethnic backgrounds. The

selection of children in the two samples

was done in two stages. First, a sample

of households was selected and then

screened to identify households

containing at least one eligible child for

the survey; then one child was selected

at random from each such household.

The sample of households selected for

screening for the NSECH was a

subsample of the households screened

for the National Immunization Survey

(NIS). Therefore, the sampling design

for the selection of households in the

NSECH is essentially the same as the

design for the selection of households in

the NIS.

Drawing the National

Immunization Survey Sample

This section describes the process

for drawing the NIS sample, including

how the frame is updated, how

telephone numbers are associated with

Immunization Action Plan (IAP) areas,

and how the NIS replicates are formed.

The process for removing businesses,

nonworking lines, and duplicate

telephone numbers from the frame is

also explained. This section is designed

for readers interested in how the NIS

frame is developed and maintained. The

description of the NSECH sample

design appears in the ‘‘National Survey

of Early Childhood Health Sample

Allocation’’ section.

Associating Telephone Numbers with

Immunization Action Plan Areas—To

draw a sample of telephone numbers in

an IAP area, one must, in effect,

compile a list of all telephone numbers

that belong to that area. For some IAP

areas this step is straightforward. For

example, when the IAP area has a single

area code, the list would consist of all

telephone numbers within the central

office codes that are in service in that

area code. (Combined, an area code and

a central-office code form a ‘‘prefix

area.’’ For example, when a telephone

number is 617–555-1234, 617–555 is

the prefix area corresponding to the 555

central office in the 617 area code.)

For other IAP areas, however, the

step encounters a number of

complications. When the IAP area is a

city, a county, or a combination of

counties, some prefix areas may cover

part of the IAP area and part of an

adjacent IAP area. In such situations, the

NIS applies a plurality rule: If at least

50% of the directory-listed households

in a prefix area fall inside an IAP area,

the prefix area is assigned to that IAP

area.

Drawing the Initial National

Immunization Survey Sample—The

sample frame for an IAP area consists

of banks of 100 consecutive telephone

numbers within the prefix areas assigned

to the IAP area. For example, the

numbers from 617–555-7100 to

617–555-7199 constitute a working bank

in the 617–555 prefix area. Banks that

contain zero directory-listed residential

telephone numbers are excluded from

the frame because they have very little

chance of containing working residential

numbers. For this preliminary step, the

GENESYS Sampling System (a

proprietary product of Marketing

Systems Group) uses a file of

directory-listed residential numbers from

Donnelley Marketing Information

Services (DMIS). The result is a file

that lists the remaining banks (the ‘‘1+

working banks’’). From the 1+ working

banks, a random sample of complete

10-digit telephone numbers is drawn for

each quarter in such a way that each

number has a known and equal

probability of being selected.

Updating the National Immunization

Survey Sampling Frame—The set of

telephone banks with at least one

directory-listed residential telephone

number changes over time. As a result,

the sampling frame of 1+ working banks

also needs to be updated. The recent

phenomenon of frequent area-code splits

has produced additional changes to the

sampling frame. The GENESYS

database reflects those changes in a

quarterly update. Marketing Systems

Group has developed a separate

sampling frame for each IAP area.

Quarterly, the database is examined to

determine whether currently included

banks should be assigned to different

IAP areas and to assign newly included

banks to IAP areas. The rules for

assignment are the same as in the initial

definitions of the IAP areas.

Once all modifications have been

made to the GENESYS database, a

number of checks ensure that all

changes have been applied correctly and

that the new database produces samples

that are consistent with those produced

before the changes. These checks

compare the number of active banks and

RDD-selectable lines in each IAP area

before and after the update. In parallel,

the actual exchanges assigned to each

IAP area before and after the update are

compared. Small changes are

expected—new banks are put into

service as new numbers are assigned. In

the event of a major discrepancy in any

of these checks, Marketing Systems

Group is notified of the difference and

asked to provide documentation of the

reasons for the change.

Forming National Immunization

Survey Sample Replicates—The total

size of the initial sample selected for an

IAP area is calculated according to the

formula:

Total sample size = (1.5)T/(AC),

where:

T is the quarterly target number of

completed NIS interviews for the

IAP area (this target number of

completes ranges from 101 to 129);

A is the proportion of telephone

numbers that remain after

identifiable business and
Series 1, No. 40 [ Page 19

nonworking numbers have been

removed (as discussed below); and

C is the proportion of telephone

numbers sent to the interviewers in

the telephone center that result in a

completed interview.

In the formula, A and C are specific

to the IAP area, and they are adjusted

each quarter, taking into account the

results from previous quarters. The

target, T, may also reflect the results in

the previous quarters; for example, if the

three previous quarters have not

produced their target total of completes,

T is raised accordingly. The factor 1.5

allows for variation in actual

performance among IAP areas and

among quarters.

The total sample selected is then

randomly divided into 26 replicates; the

first 24 are equal in size, and the last 2

are one-half that size. Each replicate is,

in effect, a random sample of the

randomly selected overall sample.

Because replicates are released to the

telephone center individually, this

procedure permits smoother release of

the sample (at the rate of one or two

replicates per week) for each IAP area

separately, as needed. Toward the end of

the quarter, the half-size replicates allow

tighter control over the total amount of

sample released. The aim is to produce

an even distribution of work in the

telephone center over the course of a

quarter and to give all cases an equal

probability of being completed.

Removing Business and Nonworking

Numbers—In a traditional random-digitdialed (RDD) survey, all sampled

telephone numbers are given to

interviewers for dialing. Because over

one-half of all selected telephone

numbers are businesses or are

unassigned, a large part of the

interviewers’ efforts may be directed

simply to identifying and removing

these numbers from the active sample.

Marketing Systems Group has produced

companion products to their GENESYS

Sampling System that can quickly and

accurately reduce the size of this task.

First, the selected sample is

matched against a GENESYS data file

that contains telephone numbers that are

directory-listed in a business yellow

pages and are not directory-listed in a

residential white pages. Any business

numbers so identified are removed from

the sample.

Second, numbers listed in

residential white pages are identified

and temporarily set aside.

Third, a hardware system,

GENESYS-ID Plus, screens the

remaining sample to remove a portion

of the nonworking numbers. Using

personal computers with special

hardware and software, this system (the

‘‘autodialer’’) automatically dials the

telephone numbers to detect nonworking

numbers. This is indicated by the

familiar tritone signal for out-of-service

numbers, by an extended period of

silence, or by continuous noise on the

line. If the telephone number being

dialed starts to ring, GENESYS-ID Plus

hangs up immediately. (Fewer than 4%

of the numbers dialed actually ring at

the receiving end.) To further reduce the

chance of annoyance if a residential

number rings, the white pages

directory-listed numbers identified in

step two are not dialed, and the

GENESYS-ID Plus equipment is

operated only during daytime hours on

weekdays.

Finally, the residential white pages

directory-listed numbers are combined

with those that were not removed by the

auto-dialers to produce the sample for

the telephone center. Together these

steps cull out approximately 18 to 20% of

the sampled lines in the NIS sample.

Obtaining Addresses for Advance

Letters—To obtain addresses that

correspond to telephone numbers in the

sample, the numbers for each replicate

are sent to a computerized name-andaddress-locating service. This

commercial service uses a database of

over 140 million residential and

business telephone numbers, and

includes approximately 30 million

unpublished telephone numbers. In some

instances, by customer preference, a

listing may not contain a street address.

The resulting file contains both numbers

with and without listing matches.

Matched listings contain a business or

residential identifier.

‘‘Do Not Call’’ Requests—The NIS

maintains a file containing telephone

numbers of people who have requested

that they not be called. Each quarter’s

sample is compared with this file, and

numbers in the ‘‘Do Not Call List’’ are

not included in the quarterly sample of

numbers loaded into the CATI system.

Duplicate Telephone Numbers—

Because of the repeated quarterly

selection of sample in each IAP area, it

is possible that some telephone numbers

will be selected more than once. To

avoid respondent problems created by

recontacts for the same survey, a further

processing step unduplicates the sample

numbers selected for the NIS. Each

complete replicate sample file is

compared with all sample files released

during the four previous quarters.

Detailed records are kept of all area

code splits to ensure accurate

unduplication. The duplicate numbers

are then classified into one of four

categories, based on final disposition

codes from earlier quarters:

1) Immunization interview fully or

partially completed

2) Ineligible household

3) Final refusal household

4) All other final dispositions, such as

nonworking, out-of-scope,

nonresidential, and noncontact.

Lines in category 4 are not

permanently resolved, so they are

combined with the unique numbers and

are treated as such by telephone

interviewers. Lines in category 3 remain

in the sample, but they are marked for

the current quarter as final refusals. This

procedure ensures that those households

will not be disturbed, but they are still

counted in the study’s statistics.

Duplicate lines in categories 1 and 2

receive special handling by interviewers.

National Survey of Early

Childhood Health Sample

Allocation

To determine the number of

telephone numbers that the NSECH

should select, it was necessary to

determine the number of completed

interviews required in each IAP area to

produce national estimates. First, the
Page 20 [ Series 1, No. 40

national sample of 1,200 children

(households) was allocated among IAP

areas in proportion to the estimated

number of households with children

between 19–35 months of age in the

IAP area, based on data from the

National Immunization Survey.

Let Mh denote the estimated number

of households with children between

19–35 months of age in the hth IAP

area, and let

78

M = ∑ Mh h = 1

denote the estimated total number of

households with children over all 78

IAP areas.

Let mh denote the number of

children that we want to select in the

hth IAP area. Under proportional

allocation,

Mh mh = 1200 M

Assuming that the ratio of the

number of children between 4–35

months of age to the number of children

between 19–35 months of age varies

little among IAP areas, this allocation

gives every household with children

between 4–35 months of age

approximately the same probability of

being included in the main sample.

Two different allocation schemes

were considered for the NSECH sample

of the 800 black non-Hispanic or

Hispanic children. (For reading ease,

these children will hereafter be referred

to as minority children, though this

population is not inclusive of all

minority races and ethnicities.) The first

scheme was simply to allocate the

sample among IAP areas in proportion

to the estimated number of households

with minority children. However, from a

practical standpoint, this allocation does

not take into account the density of

minority households in each IAP area.

Therefore, in some IAP areas in which

the proportion of minority households is

low, a very large number of households

would have to be screened to identify

those with minority children, thus

increasing the time and cost for the

survey.

The second allocation scheme that

was considered (and adopted) takes into

account the density of the minority

population in each IAP area. In this

approach, the density-eligibility rate is

defined as the number of minority

households with eligible children in an

IAP area divided by the total number of

eligible households. This eligibility rate

varies widely among IAP areas. For the

same number of telephone numbers

dialed, this second allocation scheme

will yield a larger number of eligible

households with minority children than

the first scheme (proportional

allocation). In other words, for the same

overall sample of minority households, a

smaller screener sample of households is

needed. The allocation is described as

follows:

Let Nh be the number of minority

households with children between 19–35

months of age in the hth IAP area.

Let en = Nh / Mh be the eligibility rate or

the proportion of minority households in

the hth IAP area.

Then the number of minority

children between 4–35 months of age

needed to sample from the hth IAP area

is given by

Nh√eh nh = 800

78

∑ Nh√eh

h = 1

This allocation gives a larger

sample than proportional allocation in

IAP areas in which the eligibility rates

are high. Because greater variability is

generally expected among minority

children in IAP areas with larger

proportions of minority households, this

allocation helps to reduce the variance

of the overall estimates for the minority

children, as it allocates a slightly larger

sample to those areas.

As indicated earlier, this scheme

yields more minority households than

proportional allocation for the same

number of sampled telephone numbers

(13). In other words, a smaller number

of screener calls is needed to identify

the same number of minority households

without losing much precision in the

estimates. This allocation actually

minimizes both cost and variance (that

is, this allocation minimizes cost when

the target variance is held constant, and

minimizes variance when the total cost

is held constant). It was initially

estimated that 15% fewer telephone

calls would be made than otherwise

using proportional allocation of the total

sample of minority households.

The number of households required

to be screened to achieve the desired

number of households in the main

sample and the oversample, was

computed using the NIS eligibility rates

for households with children and

households with minority children in

each IAP area. Then the initial number

of telephone numbers required to obtain

the desired number of screener

households in each IAP area was

determined.

This sample of telephone numbers

was selected from the sample already

selected for the NIS in each IAP area.

These numbers were designated as

belonging to both the NSECH sample

and the NIS sample.

Sample Selection

A subsample of the telephone

numbers designated for the NSECH

survey was selected for the main

sample. These numbers were called in

an attempt to identify households and to

establish study eligibility in those

households. For the main sample, any

household with at least one child

between 4–35 months of age was

considered eligible. An eligible child

was then selected at random from the

household. The remaining telephone

numbers were designated for the

oversample, and were used to identify

households with minority children

between 4–35 months of age; one

minority child was selected at random

from these eligible households.

In some IAP areas, the NSECH

required more than one quarter of NIS

sample. Because sample selection in

each quarter is independent in the NIS,

some numbers were selected in the first

quarter of 2000 and some numbers in

the second quarter. The split between

the two quarters varied among IAP

areas.

The population of telephone

numbers changed little between the two

quarters. Therefore, for computing base

sampling weights, the overall probability

of selection was computed assuming
Series 1, No. 40 [ Page 21

that there were no major changes in the

sample (and population of telephone

numbers) between the two quarters.

Computing weights independently in the

two quarters would have resulted in

large and widely varying weights within

an IAP area, with no indication that the

numbers called in either quarter were

different with respect to characteristics

under study.

Sampling Weights

To produce population-based

estimates, each respondent child for

whom complete data were available was

assigned a sampling weight. These

sampling weights compensate for

varying probabilities of selection of

children because of stratification by IAP

area and clustering of children within

households. Also, the weights are

needed to account for nonresponding

households and for noncoverage of

households without telephones (i.e., only

households with telephones are included

in the sampling frame).

The sampling weight combines the

following:

+ The IAP area base weight, which

reflects the probability of selecting

the household telephone number

+ An adjustment for households with

multiple telephone numbers

+ Adjustments for unit nonresponse at

various phases of identification and

data collection

The method of determining the overall

weight for each respondent child in the

survey is described in the following

section.

Base Sampling Weight

As indicated earlier, first a single

sample of telephone numbers was

selected in each IAP area. The base

sampling weight is determined by first

computing the probability of selection of

the household either in the first quarter

or in the second quarter, and then the

reciprocal of this probability. A

telephone number selected in the first

quarter is not again selected for data

collection in the second quarter.

Therefore, if the probability of selection

of a telephone number in the hth IAP

area in the first quarter is p1h, the

probability of selection of the same

number in the second quarter is

(1 – p1h ) p2h, where p2h is the

conditional probability of being selected

in the second quarter (given

nonselection in the first). If w1h and w2h

are the reciprocals of p1h and p2h,

respectively, the base weight for a

respondent child in the hth IAP area is

computed as

w1hw2h

wh = (w1h + w2h – 1)

Because the selection of telephone

numbers uses simple random sampling,

the probabilities of selection in each

IAP area are simply the number of

telephone numbers selected divided by

the total number of telephone numbers

available for selection.

Multiple-Telephone Households

The base sampling weight of

eligible households that have multiple

voice-use telephone lines was adjusted

to compensate for the higher probability

of selection of these households. The

adjustment divides the base sampling

weight by the number of telephone lines

in that household.

Let the number of telephone lines in

household i in IAP area h be Ahi. The

adjusted weight is

wh

whi = Ahi

If the household has only one

telephone line, the adjusted weight is the

same as the base sampling weight.

Unit Nonresponse Adjustment 1

(Residential Status Unknown)

When a selected telephone number

is called, three results are possible:

+ The number called is determined to

be a household

+ The number called is determined not

to be a working residential number

(It could be a business number or

nonworking number.)

+ There is nonresponse to the

screening attempt, and therefore the

status of the telephone number is

unknown

The determination that the number

called is not a working residential

number, or that the status is unknown,

was made only after several call

attempts. The method of adjusting the

base sampling weight to account for

possible residential numbers in the third

category described earlier was the same

as the method used in the NIS. This is

described in detail in the 1994 NIS

Methodology Report (9). In the NIS,

information external to the survey is

used to reallocate these unknown

numbers to either residential or

nonresidential numbers.

Let the number of telephone

numbers in each of the three categories

be nh1, nh2, nh3, respectively.

The first nonresponse adjustment

factor is

nh1 + nˆh31 bh = nh1

where nˆh31 is the estimated number of

households in the ‘‘status unknown’’

category. The procedure for estimating

nˆh31 is based on a study conducted in

1994 in which telephone company

business offices were asked to report on

the status of a sample of category 3

telephone numbers (14). The results of

the study showed that the proportion of

residential numbers varies according to

the region, whether the telephone

number was directory-listed, and the

type of noncontact (e.g., ring-no-answer

versus an answering machine).

Therefore, the nonresponse adjustment

bh was calculated within each IAP area

for a set of cells defined by region,

disposition code and whether the

number is directory-listed. To keep the

notation simple, the adjustment factor is

still denoted by bh though it could differ

for households within the IAP area.

The nonresponse-adjusted base

sampling weight after nonresponse

adjustment 1 is bhwhi.

Unit Nonresponse Adjustment 2

(Households of Unknown

Eligibility)

A second form of nonresponse may

occur because a household does not

complete the screener questions. For

these telephone numbers, identified as
Page 22 [ Series 1, No. 40

belonging to a household, there was no

determination of eligibility. A

description of the adjustment for this

form of nonresponse follows.

First, the total number of

households screened from both the main

sample and the oversample was

identified. Let the number of households

screened in the main sample be mh1 and

in the oversample be mh2. We have

nh1 = mh1 + mh2

Next, the total number of eligible

households for the main sample was

determined. Screening the households in

the main sample produced three groups

of households.

Main Sample Group 1—Eligible

households. These are households

containing at least one child between

4–35 months of age. Let the number of

such known households be qh1. It is not

possible at this stage to divide this

group into minority and nonminority

households, as no information was

collected on race/ethnicity of children in

the household.

Main Sample Group 2—Ineligible

households. These are households not

containing a child 4–35 months of age.

Let qh2 denote the number of ineligible

households.

Main Sample Group 3—Households of

unknown eligibility. Let qh3 be the

number of households whose eligibility

is unknown. We then have

mh1 = qh1 + qh2 + qh3

Let qˆh31 denote the estimated

number of households with eligible

children in the third group. This is

estimated by applying the proportion of

eligible households among known

eligible and ineligible households in

group 3.

The nonresponse adjustment for the

main sample is given by

qh1 + qˆh31

ch = qh1

where

qh1

qˆ31 = Fqh1 + qh2

Gqh3

ch can also be expressed as

mh1

ch = qh1 + qh2

The nonresponse-adjusted sampling

weight for households in the main

sample after nonresponse adjustment 2

is chbhwhi.

Similarly, as a result of screening

the households in the oversample, we

have four groups:

Oversample Group 1—Eligible minority

households, i.e., those eligible to be

included in the oversample. Let the

number of such households be uh1.

Oversample Group 2—Nonminority

households with an age-eligible child,

i.e., those not eligible to be included in

the oversample because of nonminority

status. Let the number of such

households be uh2A.

Oversample Group 3—Age-ineligible

households. Let the number of such

households be uh2B. Let uh2 =

uh2A + uh2B represent the number of

ineligible households in the oversample.

Oversample Group 4—Households of

unknown eligibility. These households

may contain age-eligible minority

children, age-eligible nonminority

children, or no children of eligible age.

Let the number of such households be

uh3.

The adjustment factor for possible

eligible households in group 4 is

uh1 + uˆh31 dh = uh1

where

uˆh31 = Suh1

u

+

h1

uh2

D uh3

dh can also be written as

mh2 dh = uh1 + uh2

The nonresponse-adjusted base

sampling weight for households in the

oversample is dhbhwhi.

Subsampling Adjustment

This adjustment accounts for the

fact that households with age-eligible

minority children were selected in both

the main and the oversample, whereas

households with only nonminority

children were selected only in the main

sample. Therefore, the base sampling

household weights for nonminority

children in the main sample have to be

increased to account for nonminority

households in the oversample. The

subsampling adjustment was determined

as follows.

First, we estimated the number of

nonminority households among the

estimated number of eligible households

in the main sample by applying the

proportion of number of nonminority

interviewed children among all

interviewed children in the main sample

to the total estimated number of eligible

households in the main sample.

Among the children interviewed in

the main sample in an IAP area, let the

number of nonminority children be zhx

and the number of minority children be

zhy. The estimated number of

nonminority households in the main

sample is given by

qˆh1A = Fzhx

z

+

hx

zhyG [qh1 + qˆh31] 

Second, we estimated the number of

eligible nonminority households in the

oversample.

The estimated number of eligible

nonminority households among

households in group 4 (households with

unknown eligibility) is given by

uˆh2A = Fuh1

uh

+

2A

uh2

G uh3

An adjustment to the household

weight for households with nonminority

children in the main sample to account

for the fact that we did not select

households with nonminority children in

the oversample is given by

qˆh1A + uh2A + uˆh2A ssha = qˆh1A

The adjusted base sampling

household weight for nonminority

children in the main sample is

sshachbhwhi.

The adjusted sampling household

weight for minority children in the main

sample is unchanged and is chbhwhi.
An Example of Subsampling

Adjustment

Assume that there are 100 identified

households in the total sample. Let 60

of these households be in the main

sample and 40 of them be in the

oversample. These are households to be

screened for the study.

Main Sample Adjustments—The 60

main sample households are screened

with the following results:

+ 20 eligible households,

+ 30 ineligible households, and

+ 10 households of unknown

eligibility.

The estimated number of eligible

households in the unknown category is

(20/50) x 10 = 4. Therefore, the

estimated number of eligible households

in the main sample is 20+4=24. The

nonresponse adjustment 2 for the main

sample is (24)/20 = 1.2.

Assume that after the children in

the selected households in the main

sample have been interviewed, there are

15 nonminority and 5 minority children

in the main sample. The proportion of

nonminority children is 15/20. If this

proportion is applied to the estimated 24

households in the main sample, the

estimated number of nonminority

households in the main sample is

(15/20) x 24 = 18.

Oversample Adjustments—The 40

oversample households are screened

with the following results:

+ 5 minority households

+ 10 nonminority households

+ 10 age-ineligible households

+ 15 households of unknown

eligibility

The estimated number of

nonminority households in the unknown

category is (10/25) x 15 = 6.

Therefore, the estimated number of

nonminority households in the

oversample is 10+6=16.

To account for 34 (18 + 16)

households using the 18 in the main

sample, the subsampling adjustment for

nonminority children in the main sample

is (18 + 16)/18 = 1.89.

When the nonresponse 2 adjustment

of 1.2 in the main sample and the

subsampling adjustment of 1.89 to the

15 children in the main sample are both

applied, the estimated total number of

nonminority households in the overall

sample is 34.

Unit Nonresponse Adjustment 3

(Nonresponse by Eligible

Households)

A household in the main sample

was considered a nonrespondent if it

was eligible, but data regarding a child

from the household were not obtained.

The weights of other responding

households were increased to account

for this nonresponse. These adjustments

are made within an IAP area.

Among the known eligible

households in the main sample (qh1), let * qh1 be the number of households who

completed an interview. In the * oversample, let uh1 be the number of

responding households out of uh1 . The

adjustment factors for nonresponse to

data collection in the main sample and

the oversample are then

qh1 uh1 and * * qh1 uh1

The final nonresponse-adjusted

household weight for nonminority

children in the main sample is the

product of the adjustments and weights

described thus far:

* whi = chbhwhisshaS

qh1

*D qh1

and the household weight for a minority

child in the main sample is

whi

m = chbhwhiS

qh1

*D qh1

The nonresponse-adjusted household

weight for minority children in the

oversample is

o whi = dhbhwhiS

uh1

*D uh1

Adjustment of Household

Weights to Known Control

Totals

Adjusting the household weights so

that the sum of the weights agrees with

known population control totals was

Series 1, No. 40 [ Page 23

considered. One characteristic

considered for the control total was

household size. The weighted household

size of households containing children

between 0–2 years of age from the

Current Population Survey (CPS) for

1999 and 2000 was compared with the

weighted household size in the NSECH.

There are no large differences

between the NSECH and the CPS in the

distribution of households by size. In

fact, the estimated distributions from the

CPS also vary from 1 year to the next.

Because these are estimates and cannot

be considered as solid control totals, it

was decided not to adjust the household

weights at this stage.

Child Weights

Next, the child-level nonresponseadjusted sampling weights were created.

Let the number of children between

4–35 months of age in a selected

household (say the ith household) in the

main sample be thi. Because one child is

selected at random, the weight for a

nonminority child in the main sample is

given by

* whi*c = whi thi

Note that the weight is the same as

the adjusted household weight (whi

*

)

except that households with more than

one eligible child are given

proportionately a greater weight than

households with only one eligible child.

If the child is a minority child, the

weight is given by

mc wh1 = whimthi

o Let thi be the number of minority

children in a household in the

oversample. The child weight for a

respondent child in the oversample is

then

oc o whi = whio

thi

Adjustment for Noncoverage of

Nontelephone Households

The NSECH is a survey of

telephone households, so the probability

of selection for households with no

telephones at the time of the survey is

zero. Therefore, the results of this

survey may be biased if no adjustment
Page 24 [ Series 1, No. 40

is made for noncoverage of

nontelephone households. Although the

customary poststratification adjustments

by race, age, and sex will adjust to

some degree for noncoverage, it

assumes that telephone and

nontelephone households in each cell

are similar with respect to the

characteristics under study. Therefore,

the sampling weights are adjusted to

account for households that did not have

telephone service at the time of the

survey in addition to the

poststratification adjustments. Evidence

suggests that households with telephones

at the time of the survey, but with

interruptions in telephone service during

the preceding year, are more similar to

households with no telephone service at

the time of the survey than households

with uninterrupted telephone service

during the year (12). The adjustment for

noncoverage of nontelephone

households uses data on interruption in

telephone service obtained from the

respondent households in the sample.

The procedure for adjusting the weights

consisted of the following steps (11, 15).

Step 1—The weighted percent of

children between 4–35 months of age

coming from households with

interruptions in telephone service was

obtained. This is estimated by taking the

ratio of the estimated number of

children from households with

interruption to the estimated total

number of children between 4–35

months of age. This survey estimate was

obtained using the child-level

nonresponse-adjusted sampling weights.

Let the proportion with interruptions in

service be It .

Step 2—From 2000 CPS data, the

percent of children between 0–2 years

of age coming from households with

telephones and without telephones was

obtained. Let rt be the proportion of

children from telephone households.

Step 3—The total number of

children between 4–35 months of age

was obtained from the National Vital

Statistics System control totals counting

children born in the United States

between May 1997 and December 1999.

Let N be the total number of children

between 4–35 months of age from the

vital statistics records.

Step 4—The percent of children from

telephone households was applied to the

total obtained in step 3 and the total

number of children was split into two

groups. The numbers of children in

telephone and nontelephone households

are given, respectively, by Nt = Nrt and

No = N – Nt.

Step 5—The following two control

totals were formed:

+ The number of children in telephone

households with no interruptions in

service during the entire year

+ The number of children in

nontelephone households or in

telephone households that had an

interruption in service.

The two totals are Nt – Nt It and No + Nt

It. These totals are used to adjust the

weights of children from households

with interruptions in telephone service

along with poststratification weight

adjustments.

Poststratification

To compensate for potential biases

due to noncoverage and nonresponse,

poststratification adjusts the weights to

match population control totals for

combinations of key demographic

variables (such as race, sex, age,

mother’s education, and income)

obtained from an independent source.

Two sources were considered for the

number of children between 4–35

months of age by age, sex, and race.

The first was the U.S. Census Bureau

projection by single years of age by

race/ethnicity and sex. The other was

the vital statistics records, which also

give information on age, race/ethnicity,

and sex. In addition to this information,

data are also available on mother’s

education in the vital statistics records.

No independent source could be

identified that would provide income

data using questions similar to those

used in this survey.

In the U.S. Census Bureau

projections, the number of children

between 0–12 months of age were

adjusted to get the number between

4–35 months of age. More importantly,

no information on mother’s education is

available through the U.S. Census

Bureau. Therefore, if the U.S. Census

Bureau source were used, an additional

source, such as the CPS, would be

required for data on mother’s education.

It was thought that mother’s education

might be an important poststratification

variable in the absence of

poststratification on household income.

Household income may be correlated

with mother’s education and many of

the health characteristics of interest in

the survey may also be related to

mother’s education. For these reasons

and because the NIS currently uses vital

statistics records to create control totals

for poststratification adjustment, the

vital statistics records were used to

derive the control totals.

For NSECH, the independent source

was the vital statistics count of children

born in the United States between May

and December of 1997 and all months

of 1998 and 1999. This range of birth

months was obtained by using the

midpoint of the NSECH data collection,

April 2000. Adjusting the weights based

on these population control totals for

age, sex, race, and mother’s education

helps compensate for any potential

noncoverage and nonresponse biases.

These counts were adjusted for

infant mortality, immigration, and

migration between IAP areas. The

adjustments to the vital statistics data

are the same ones used by the NIS to

poststratify the NIS weights. See chapter

8 of the 1994 NIS Methodology Report

(9). These adjustments are necessary

because the use of the raw (unadjusted)

natality data file to form the required

population control totals for the NIS has

three significant limitations. The third

limitation is not applicable to NSECH,

but is mentioned here in the interest of

full disclosure. The adjustment based on

this limitation has no effect on the

population control totals used for

NSECH.

First, the natality file provides a

universe of live births, and therefore it

does not reflect a reduction in the

population of children from infant

mortality. To adjust for this reduction in

the population, 1989 State-specific

infant mortality rates (deaths under 1

year) by race group (white versus

nonwhite) were applied to the vital
Series 1, No. 40 [ Page 25

statistics data. Of course, these rates do

not relate directly to the 1997–99 birth

cohort, but were used because they

relate directly to the 1990 Census data

used for the immigration adjustment

(see next paragraph). It should be noted

that mortality in the second and third

years of life has not been taken into

account. However, this mortality is

unlikely to have much impact on the

population control totals.

Second, the natality file will not

reflect children born outside the United

States who immigrate to this country

before reaching 19–35 months of age.

This immigration will increase the

population size of children, but the

effect is likely to vary considerably

from IAP area to IAP area. For the NIS,

the Public Use Microdata Samples

(PUMS) from the 1990 Census were

used to estimate by age group the

number of 2-year-olds in each State who

were born outside the United States.

Third, the natality file records State,

county, and city of residence at time of

birth. Children may move from one IAP

area to another by the time they reach

19–35 months of age. 1990 Census data

were used to estimate the percentage of

2-year-old children who had been born

outside their state of residence at the

time of the 1990 Census enumeration. A

different State 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

is 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. This inter-IAP-area migration

might reduce or inflate the population

control totals for a given IAP area. The

1990 Census data, however, allow us to

estimate net migration only for states,

and not for individual IAP areas. Given

the limitations of the data, a simple

State-by-State adjustment for net

migration was made for each race

group.

To estimate in-migration, the 1990

PUMS was used to estimate the

proportion of 2-year-olds living in State

X that were born in a different State in

the United States. This proportion

reflects in-migration and also mothers

who resided in State X at the time of

the birth but gave birth in a different

State. To remove the latter component,

this proportion was multiplied by the

vital statistics proportion of births to

mothers residing in State X who gave

birth in State X. To estimate outmigration, the PUMS was used to

estimate the proportion of 2-year-olds

born in State X but who no longer live

in State X. This proportion reflects

out-migration and also mothers living

outside State X who gave birth in State

X. To remove the latter component, this

proportion was multiplied by the vital

statistics proportion of births occurring

in State X among mothers who resided

in State X. Net migration then equals

in-migration minus out-migration. This

NIS Vital Statistics adjustment does not

affect the national control totals for the

NSECH.

The infant mortality and

immigration adjustments have a small

impact on the vital statistics control

totals, as shown in table D.

Fifty-four cells were created by

taking the cross-classification of three

categories of mother’s education, three

age categories for children, three

race/ethnicity categories, and two

categories for sex of child. The 54 cells

were collapsed into 39 categories

because the sample sizes in some cells

were too small, giving rise to very large

weights.

The totals by age x race x sex x

mother’s education are known, but the

corresponding subtotals for the

telephone and nontelephone categories

are unknown. Therefore, the weights are

adjusted to agree with the known totals

through raking. Raking is a

poststratification procedure that can be

used when poststrata (control totals) are

formed using more than one variable

and only the marginal totals are known.

It consists of adjusting the weights

iteratively so that the sum of the

weights agrees with the totals in the

margins. For example, first the weights

in each cell are adjusted such that the

sum of the weights equals the 39

poststratification totals in one margin.

Then, weights are adjusted such that

they agree with the column totals. After

a few iterations, the sums of the weights

agree with row totals and column totals.

In the NSECH, the sums of the weights

agree with row totals by race x sex x

education x age and the total telephone

and nontelephone populations in the

columns. The total weighted number of

children is the same as the control total

of 10,726,319.

After raking, the weights were

examined to identify any extremely

large weights. These weights affect the

variance of the estimates. A decision

was made to trim weights that exceeded

the median weight plus roughly 6 times

the interquartile range. The outlier

weights were trimmed to be equal to the

median plus 5.8 times the interquartile

range. The raking procedure was applied

again using the trimmed weights to

ensure that the sums of the weights

agree with the known control totals.
Page 26 [ Series 1, No. 40

Appendix II

Related Survey

Content and

Sources of Questions

Source for Item,

Question or Surveys with

Item# Content Item Text Related Content

Health Care Utilization

A1Q01 Number of total

health care

visits

A1Q02 # of well child

check ups

A1Q03 Location of

well-child care

A1Q04 Is there any

regular provider

A1Q05 Usual kind of

regular provider

A1Q06 Urban/rural of

usual provider

A1Q07 Gender of

provider

A1Q10 Selection of

provider

How many times has (CHILD) been to any doctor or other MEPS,

healthcare provider for any reason? Please include all visits that NHIS, PHDS+,

were made when (CHILD) was sick, or needed a shot or a check- PSID-CD

up.

Well-child care visits are visits that are made to a doctor or NHIS

healthcare provider who takes care of (CHILD) when (his/her) is

not sick, but needs a check-up or a shot. (In the last 12 months/

Since CHILD’s birth), how many times has (he/she) had a wellchild visit for a check-up or shot?

When (CHILD) needs a shot or a check-up, where do you usually CWF-SPYC,

take (him/her)? NS-CSHCN

Is there a particular doctor or other healthcare provider that you NHIS, PHDS+

usually take (CHILD) to for well-child care? By healthcare provider

I mean any nurse, nurse practitioner, physician assistant or other

person who may have provided healthcare to (CHILD).

What kind of healthcare provider(s) does (CHILD) usually see for NHIS, PHDS+

well-child care, that is for check-ups and shots? Is (his/her)

healthcare provider a pediatrician, family practitioner, pediatric

nurse practitioner, physician’s assistant, or some other health

professional?

Which of the following would best describe the location of your CWF-PDS

child’s (HEALTHCARE PROVIDER)’s clinic or practice?

PHDS+

Is this (HEALTHCARE PROVIDER) a man or a woman?

How did YOU start taking (CHILD) to (his/her) current CPRQ, MEPS

(HEALTHCARE PROVIDER)?

Our appreciation is extended to Moira Inkelas, Ph.D.; Harvinder Sareen, M.P.H.; and Janel Wright, from the University of California, Los Angeles, for preparing

this appendix.
Series 1, No. 40 [ Page 27

Source for Item,

Question or Surveys with

Item# Content Item Text Related Content

Parental Perception of Care

A2Q01 Visit length

A2Q03 Ability to ask

questions

A2Q05 Satisfaction

w/check ups on

1–10 scale

A2Q08 Child’s health

rated

Interactions with Healthcare Providers

A3Q01 Breastfeeding

(under 10

months )

A3Q02 Issues related to

food/feeding

(under 10

months)

A3Q03 Child’s sleeping

positions (under

10 months)

A3Q04 / Night waking

A3Q13 and fussing

(4 to 18 months)

A3Q05 How child

communicates

needs (under

10 months)

A3Q06 Burn prevention

(under 10

months)

A3Q07/ Using a car seat

A3Q20/ (all ages)

A3Q33

A3Q08/ Child care

A3Q21/ arrangements

A3Q34 (all ages)

A3Q09/ Importance of

A3Q22/ reading

A3Q35 all ages)

A3Q12/ Issues related to

A3Q25 food/feeding

(10 to 35

months)

A3Q14 Sleeping with a

bottle (10 to 18

months)

A3Q15 Weaning from a

bottle (10 to 18

months)

A3Q16/ Words and

A3Q29 phrases child

understands

(10 to 35 months)

Let’s talk about the well-child care (CHILD) has received (in the

last 12 months/since [his/her] birth). Think about the last time you

took (CHILD) for a check-up. How long was the doctor or

healthcare provider who examined (CHILD) in the room with you?

During (CHILD)’s last check-up, did you ask all the questions you

wished to ask?

How would you rate (CHILD)’s check-ups (during the last 12

months/since [his/her] birth). Please include all the doctors,

nurses, and other health providers that (CHILD) may have seen.

Use any number from 0 to 10 where 0 is the worst healthcare

possible and 10 is the best healthcare possible.

In general, how would you describe (CHILD)’s health? Would you

say (his/her) health is excellent, very good, good, fair, or poor?

Since (CHILD)’s birth, have (his/her) doctors or other healthcare

providers talked with you about breast-feeding?

Since (CHILD)’s birth, did (his/her) doctors or other healthcare

providers talk with you about issues related to food or feeding

(CHILD) such as the introduction of solid foods?

Since (CHILD)’s birth, did (his/her) doctors or other health care

providers talk with you about (CHILD)’s sleeping positions?

Since (CHILD)’s birth, did (his/her) doctors or other health care

providers talk with you about night waking and fussing?

Since (CHILD)’s birth, did (his/her) doctors or other health care

providers talk with you about how (CHILD) communicates (his/

her) needs?

Since (CHILD)’s birth, did (his/her) doctors or other health care

providers talk with you about burn prevention methods, such as

changing hot water temperatures in your home?

Since (CHILD)’s birth, did (his/her) doctors or other health care

providers talk with you about using a car-seat?

Since (CHILD)’s birth, did (his/her) doctors or other health care

providers talk with you about childcare arrangements?

Since (CHILD)’s birth, did (his/her) doctors or other health care

providers talk with you about the importance of reading to

(CHILD)?

(In the last 12 months/since [his/her] birth), did (CHILD)’s doctors

or other health care providers talk with you about issues related to

food or feeding (him/her)?

(In the last 12 months/since [his/her] birth), did (CHILD)’s doctors

or other health care providers talk with you about [his/her]

sleeping with a bottle?

(In the last 12 months/since [his/her] birth), did (CHILD)’s doctors

or other health care providers talk with you about taking (him/

her) off of the bottle?

(In the last 12 months/since [his/her] birth), did (CHILD)’s doctors

or other health care providers talk with you about the words and

phrases (CHILD) uses and understands?

CWF-PDS,

MEPS

NHIS

CAHPS

CAHPS, CWFSPYC, MEPS,

NHIS, PHDS+,

PSID-CD

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+
Page 28 [ Series 1, No. 40

Source for Item,

Question or Surveys with

Item# Content Item Text Related Content

A3Q17/ Guidance and (In the last 12 months/since [his/her] birth), did (CHILD)’s doctors PHDS, PHDS+

A3Q31 discipline or other health care providers talk with you about guidance and

(10 to 35 months) discipline techniques to use with (CHILD)?

A3Q18/ Toilet training (In the last 12 months/since [his/her] birth), did (CHILD)’s doctors PHDS, PHDS+

A3Q32 (10 to 35 or other health care providers talk with you about toilet training?

months)

A3Q19 Ipecac-poison (In the last 12 months/since (his/her) birth), did (CHILD)’s doctors PHDS, PHDS+

prevention or other health care providers talk with you about the use of syrup

(10 to 18 months) of Ipecac if your child swallows some poison?

A3Q26 Bedtime In the last 12 months, did (CHILD)’s doctors or other health care PHDS, PHDS+

routines (19 to 35 providers talk with you about (CHILD)’s bedtime routines?

months)

A3Q27 Dangerous In the last 12 months, did (CHILD)’s doctors or other health care PHDS, PHDS+

situations providers talk with you about ways to teach (him/her) about

(19 to 35 months) dangerous situations, places or items like electrical sockets, the

stove, climbing on things, or running into the street?

A3Q28 Things child In the last 12 months, did (CHILD)’s doctors or other health care PHDS

can start to providers talk with you about things (CHILD) may start to do for

do for self (himself/herself) like washing or dressing?

(19 to 35 months)

A3Q30 How child In the last 12 months, did (CHILD)’s doctors or other health care PHDS, PHDS+

learning to get providers talk with you about how (CHILD) is learning to get along

along w/other with other children?

children

(19 to 35 months)

A3Q38A Provider takes (In the last 12 months/since [his/her] birth), how often did PHDS, PHDS+

time to (CHILD)’s doctors or other healthcare providers take time to

understand understand the specific needs of (CHILD)? Would you say always,

specific needs usually, sometimes, or never?

of child

A3Q38B Provider (In the last 12 months/since [his/her] birth), how often did MEPS, PHDS,

respects parent (CHILD)’s doctors or other healthcare providers respect that you PHDS+

as expert on are the expert on your child? Would you say always, usually,

child sometimes, or never?

A3Q38C Provider asks (In the last 12 months/since [his/her] birth), how often did PHDS, PHDS+

about feelings (CHILD)’s doctors or other healthcare providers ask you about

as parent how you are feeling as a parent? Would you say always, usually,

sometimes, or never?

A3Q38D Provider (In the last 12 months/since [his/her] birth), how often did PHDS, PHDS+

understands (CHILD)’s doctors or other healthcare providers understand you

your family and your family and how you prefer to raise (CHILD)? Would you

say always, usually, sometimes, or never?

A3Q39 Did provider (In the last 12 months/since [his/her] birth), have (CHILD)’s PHDS, PHDS+

ask about doctors or other health care providers ever asked you about

violence violence in your community?

A3Q41 Did provider (In the last 12 months/since [his/her] birth), have (CHILD)’s PHDS, PHDS+

ask about doctors or other health care providers ever asked whether you or

smoker in someone in your household smokes?

household

A3Q42 Did provider (In the last 12 months/since [his/her] birth), have (CHILD)’s PHDS, PHDS+

ask about doctors or other health care providers ever asked whether you or

alcohol/drugs someone in your household drinks alcohol and/or uses drugs?

A3Q43 Did provider (In the last 12 months/since [his/her] birth), have (CHILD)’s PHDS, PHDS+

ask about doctors or other health care providers ever asked you if you have

parental someone to turn to for emotional support?

emotional

support?

A3Q46 Did physician Did (CHILD)’s doctors or other health care providers ever tell you PHDS, PHDS+

do develop. that they were carrying out—what doctors call—a ‘‘developmental

assessment? assessment’’ of (CHILD)?
Series 1, No. 40 [ Page 29

Source for Item,

Question or Surveys with

Item# Content Item Text Related Content

A3Q46A Did physician do Did (CHILD)’s doctors or other health care providers ever have PHDS, PHDS+

content of (him/her) pick up small objects or stack blocks or throw a ball or

develop. assessment recognize different colors?

A3Q47 Referrals to Doctors sometimes provide referrals to specialists or to CWF-PDS,

specialists educational or developmental programs. (In the last 12 months/ PHDS, PHDS+

by physician since [his/her] birth) has (CHILD)’s doctors or other health care

providers referred (him/her) to any specialist?

A3Q47A Kind of What kind of specialist was that? CWF-PDS

specialist

referred to

A3Q48 Referrals to (In the last 12 months/since [his/her] birth) has (CHILD)’s doctors CWF-PDS,

programs or other health care providers referred you to any program or PHDS+

and classes class?

A3Q48A Kind of program What kind of program/class was that? PHDS+

referred to

A3Q49 Childbirth class Did you attend a childbirth class before the birth of (CHILD)? CWF-SPYC

attendance

A3Q50 Parenting class Did you attend a parenting class after the birth of (CHILD)? CWF-SPYC,

attendance PHDS+

A3Q50A Insurance Was this parenting class paid for or covered by a health insurance PHDS+

payment for plan?

parenting class

attendance

A3Q51B Parenting class Did you attend a parenting class after the birth of your other child PHDS+

attendance for or children?

other children

A3Q52 Premature birth Now I would like you to think back to the time (CHILD) was born. CWF-SPYC,

of child Was (he/she) born prematurely, that is, was (he/she) more than 4 ECLS, PHDS+,

weeks early? PSID-CD

A3Q53 Birth weight of What was (CHILD)’s birth weight? ECLS, NHIS,

child PHDS+,

PSID-CD

A3Q54 Breastfeeding ever Now I am going to ask you a few questions about breastfeeding. CWF-SPYC,

Was (CHILD) breastfed for any length of time NHIS, PHDS+,

PSID-CD

A3Q54A Duration of For how many days, weeks, or months was (CHILD) breastfed? NHIS, PHDS,

breastfeeding PHDS+,

PSID-CD

A3Q55 Doctor Did (CHILD)’s doctors or other health care providers give you any CWF-SPYC

encourage help or encouragement for breastfeeding?

breastfeeding

Family Interactions and Home Safety

A4Q01A Consistent Is (CHILD)’s bedtime usually the same everyday, or does it CWF-SPYC,

bedtimes change from day to day? ECLS, PSID-CD

A4Q01B Consistent Is (CHILD)’s nap-time usually the same everyday, or does it CWF-SPYC,

nap times change from day to day? ECLS, PHDS+

A4Q01C Consistent Are (CHILD)’s mealtimes usually the same everyday, or do they CWF-SPYC,

meal times change from day to day? ECLS, PSID-CD

A4Q02 Frequency of Now I would like to talk to you about (CHILD)’s activities with you CWF-SFYC,

activities and other family members. ECLS, PHDS+,

w/child Please tell me the number of days in a typical week that you or PSID-CD

any other family members do the following things.

A4Q02X01 Read stories Read stories to (CHILD). CWF-SPYC,

ECLS, PHDS,

PHDS+, PSID-CD,
Page 30 [ Series 1, No. 40

Source for Item,

Question or Surveys with

Item# Content Item Text Related Content

A4Q02X02 Play music/sing

A4Q02X03 Take child out

A4Q02X04 Eat

midday/evening

meal together

A4Q02X05 Eat breakfast together

A4Q03 Time spent

watching TV

A4Q04 # of books

in home

A4Q05 Frustration

w/child’s

behavior

A4Q06 Satisfaction

w/amt.

of time

spent w/child

A4Q07 Discipline techniques

used

A4Q07X01 Raising voice

A4Q07X02 Spanking

A4Q07X03 Taking away

toy/treat

A4Q07X04 Time out

A4Q07X05 Explaining

A4Q08X01 Specific actions

to childproof

home: baby

gates

A4Q08X02 Locks

A4Q08X05 Hot water

A4Q09 Syrup of Ipecac

A4Q10 Hours in

childcare

A4Q11 Relative or

nonrelative

childcare

A4Q12 Location of

childcare

Parental and Child Health

A5Q01X01 Nervous

(MHI5)

Play music or sing songs with (CHILD).

Take (CHILD) on any kind of outing such as to the park, grocery

store, a church or a playground.

Eat a mid-day or evening meal together?

Eat breakfast together?

In a typical day, about how many hours does (CHILD) spend

watching TV or videos?

About how many children’s books are there in your house,

including library books? Please only include books that are for

children.

In a typical day, how often would you say you feel frustrated or

aggravated with (CHILD)’s behavior?

Now I would like to ask you about the amount of time you spend

with (CHILD). Would you say that you spend the right amount of

time with (CHILD), or would like to spend a lot more time, a little

more time, a little less time, or a lot less time?

I am going to read a list of methods of discipline parents might

use with children (CHILD)’s age. For each, please tell me if you

use that method often, sometimes, rarely, or never with (CHILD).

First, how about raising your voice or yelling?

How about spanking?

How about taking away a toy or treat?

How about giving a time-out, that is, making (CHILD) take a break

from whatever activity (he/she) is involved in?

How about explaining to (CHILD) why [his/her] behavior is not

appropriate.

I am now going to read you a list of things that parents sometimes

do to childproof their home or make it safe. For each item, tell me

if you ever did that in your home: Put up baby gates, window

guards or other barriers.

Put locks or safety latches on cabinets where things such as

cleaning agents or medicines are kept.

Turned down the hot water thermostat setting.

Syrup of Ipecac can be used if (CHILD) swallows something

poisonous. Do you have Syrup of Ipecac at home?

In a typical week, how many hours does (CHILD) spend in the

care of someone other than a parent or guardian?

Is the person who usually cares for (CHILD) a relative or a nonrelative?

[Where] Is (CHILD) mostly cared for?

How much of the time during the past month have you been a

very nervous person? Would you say all of the time, most of the

time, a good bit of the time, some of the time, a little of the time

or none of the time?

CWF-SPYC,

ECLS, PHDS+

ECLS

ECLS

ECLS

ECLS, PSID-CD

ECLS, PSID-CD

CWF-SPYC,

ECLS, PSID-CD

CWF-SPYC

CWF-SPYC

CWF-SPYC

CWF-SPYC

CWF-SPYC

CWF-SPYC

CWF-SPYC

PHDS

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

ECLS, LACHS

ECLS

ECLS, LACHS,

PSID-CD
Series 1, No. 40 [ Page 31

Source for Item,

Question or Surveys with

Item# Content Item Text Related Content

A5Q01X02 Calm and

peaceful

(MHI5)

A5Q01X03 Downhearted

and blue

(MHI5)

A5Q01X04 Down in the

dumps (MHI5)

A5Q01X05 Happy (MHI5)

A5Q02 How well

coping w/day-to-day

parenting

A5Q05X01 Concerns about

speech sounds

(PEDS)

A5Q05X02 Concerns about

vision or

hearing

A5Q05X03 Concerns about child’s

understanding (PEDS)

A5Q05X04 Concerns about ability

to use hands and

fingers (PEDS)

A5Q05X05 Concerns about

ability to use

arms and legs

(PEDS)

A5Q05X06 Concerns about

behavior

(PEDS)

A5Q05X07 Concerns about

ability to get

along (PEDS)

A5Q05X08 Concerns about

learning to do

things (PEDS)

A5Q05X09 Concerns about

learning school

skills (PEDS)

A5Q05X10 Concerns about

limitations of

activities (PEDS)

A5Q05X11 Concerns about

emotional

well-being

A5Q06 Types of

conditions

child has

A5Q07 Prescription

medicine

(CSHCN Screener)

A5Q07A Due to

condition

(CSHCN Screener)

How much of the time during the past month have you felt calm

and peaceful? Would you say all of the time, most of the time, a

good bit of the time, some of the time, a little of the time or none

of the time?

How much of the time during the past month have you felt

downhearted and blue?

How much of the time during the past month have you felt so

down in the dumps that nothing could cheer you up?

How much of the time during the past month have you been a

happy person?

In general, how well do you feel you are coping with the day-today demands of parenthood?

Sometimes parents have concerns about their children. Are you

concerned a lot, a little, or not at all about: how (CHILD) talks and

makes speech sounds (RESPONSE OPTIONS: A lot; A little; Not

at all; Don’t know)?

How your child sees or hears?

How your child understands what you say?

How your child uses his or her hands and fingers to do things?

How your child uses his or her arms and legs?

How your child behaves?

How your child gets along with others?

How your child is learning to do things for himself/herself?

How your child is learning preschool or school skills?

Whether your child can do what other children his or her age can

do?

Child’s emotional well-being?

Now I would like to ask a few questions about (CHILD)’s health.

In the last 12 months, did (he/she) have any of the following

conditions:

Does your child currently need or use medicine prescribed by a

doctor, other than vitamins?

Is this because of any medical, behavioral or other health

condition?

CWF-SPYC

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PHDS, PHDS+

PSID-CD

CAHPS, MEPS,

NS-CSHCN,

PHDS, PHDS+

CAHPS, MEPS,

NS-CSHCN,

PHDS, PHDS+
Page 32 [ Series 1, No. 40

Source for Item,

Question or Surveys with

Item# Content Item Text Related Content

A5Q07B Lasting 12+

months

(CSHCN Screener)

A5Q08 Increased

service use

(CSHCN Screener)

A5Q08A Due to

condition

(CSHCN Screener)

A5Q08B Lasting 12+

months

(CSHCN Screener)

A5Q09A Missed care

for any

reason

A5Q09B Delayed care

A5Q09C Kind of care

A5Q09DX01 Reason for

missed care

A5Q09DX02 Reason for

missed care

A5Q09DX03 Reason for

missed care

A5Q09DX04 Reason for

delayed care

A5Q09EX01 Concerns

about child’s

development

A5Q09EX02 Problems

attending

day care

A5Q09EX03 Problems

meeting work

responsibilities

A5Q10 Emergency room

utilization

A5Q11 Hospital

utilization

A5Q12 # of calls to

doctor’s office

for infor

Financial Welfare and Health Insurance

A6Q01X01 Trouble

paying for

prenatal care

A6Q01X02 Birth expenses

A6Q01X03 Child’s

health/medical

expenses

Is this a condition that has lasted or is expected to last for at least CAHPS, MEPS,

12 months? NS-CSHCN,

PHDS, PHDS+

Does your child need or use more medical care, mental health or CAHPS, MEPS,

educational services than is usual for most children of the same NS-CSHCN,

age PHDS, PHDS+

Is this because of any medical, behavioral, or other health CAHPS, MEPS,

condition? NS-CSHCN,

PHDS, PHDS+

Is this a condition that has lasted or is expected to last for at least CAHPS, MEPS,

12 months? NS-CSHCN,

PHDS, PHDS+

(During the past 12 months/since [his/her] birth) was there any MEPS, NHIS,

time that (CHILD) needed health care for a problem or concern PHDS+

but did not get it?

(During the past 12 months/since [his/her] birth) was there any MEPS, NHIS,

time that (CHILD) received care for a problem or concern, but got NS-CSHCN,

the care later than you would have liked? PHDS+

Why did (CHILD) need health care? NHIS, PHDS+

Why didn’t (CHILD) receive care for ___/Why was (CHILD)’s care MEPS, NHIS,

delayed for ____? Was it because: You could not afford it or had PHDS+

no health insurance?

You had no provider to go to for (CHILD)? MEPS, PHDS+

(CHILD)’s provider did not consider it a problem? MEPS, PHDS+

You had transportation or childcare problems or problems related MEPS, PHDS+

to work?

Did the (lack of/delay in) healthcare for (CHILD)’s ____ : Create PHDS+

concerns about your child’s future development?

Did the (lack of/delay in) healthcare for (CHILD)’s ____ : Create PHDS+

problems for your child attending day care?

Did the (lack of/delay in) healthcare for (CHILD)’s ____ : Create PHDS+

problems for you or your spouse or partner meeting work

responsibilities?

During the past 12 months, how many times has (CHILD) gone to CAHPS, PHDS+

a hospital emergency room about (his/her) health? Please include

emergency room visits that resulted in hospital admission.

During the past 12 months, how many times has (CHILD) had to NHIS, PHDS+

stay in the hospital overnight?

During the past 12 months, how many times have you called CAHPS

(CHILD)’s doctor’s office to ask a question or get some

information?

For each of the items in the list, please tell me if you had a lot of CWF-SPYC,

trouble, some trouble, or no trouble at all paying for that item. PHDS+

First, how about prenatal care during pregnancy?

How about the medical expenses for (CHILD)’s birth? CWF-SPYC,

PHDS+

How about (CHILD’s health and medical expenses? CWF-SPYC,

PHDS+
Series 1, No. 40 [ Page 33

Source for Item,

Question or Surveys with

Item# Content Item Text Related Content

A6Q01X04 Supplies (e.g.,

diapers)

A6Q01X05 Child care

A6Q02 Medicaid

A6Q03 Title V

A6Q04 S-CHIP

A6Q05 Private health

insurance

A6Q06 Military

health care

A6Q07 I.H.S.

A6Q08 Other

A6Q09 No health

insurance

A6Q09A What kind of

insurance

A6Q09B Time without

insurance

A6Q09C Amount of time

with insurance

A6Q10 Any period

without

insurance

A6Q10A Amount of time

with no

insurance

A6Q11 Limited

access plan

A6Q12 Specialist

approval

required

How about supplies like formula, food, diapers, clothes, and CWF-SPYC,

shoes? PHDS+

How about childcare? CWF-SPYC

Is (CHILD) covered by Medicaid, in this state called (FILL IN NS-CSHCN

NAME), a health insurance program for low-income families?

Is (CHILD) covered by (FILL STATE TITLE V PLAN NAME)? NS-CSHCN

Is (CHILD) covered by (FILL STATE CHIP NAME)? NS-CSHCN

Is (CHILD) covered by private insurance, that is, health insurance NS-CSHCN

obtained through employment or unions or purchased directly?

Is (CHILD) covered by military health care, CHAMPUS, CHAMP- NS-CSHCN

VA, or TRICARE?

Is (CHILD) covered by the Indian Health Service? NS-CSHCN

Is (CHILD) covered by any other kind of health insurance or NS-CSHCN

health care plan that pays for services obtained from hospitals,

doctors, and other health professionals?

It appears that (CHILD) does not have any health insurance NS-CSHCN

coverage to help pay for services from hospitals, doctors, and

other health professionals. Is that correct?

What kind of health coverage does (CHILD) have? NS-CSHCN

Was there any time (during the past 12 months/since [his/her] PSID-CD

birth) when (CHILD) did have health insurance or was covered by

a health plan?

How many months (during the past 12 months/since [his/her] PSID-CD

birth) did (CHILD) have health insurance?

Was there any time (during the past 12 months/since [his/her] NS-CSHCN

birth) when (CHILD) did not have health insurance or was not

covered by a health plan?

How many months (during the past 12 months/since [his/her] NS-CSHCN

birth) did (CHILD) not have health insurance?

Are you required by your health insurance company to sign up MEPS, PSID-CD

with a certain primary care doctor, group of doctors, or certain

clinic which (CHILD) must go to for all of his/her routine care?

If (CHILD) needs to go to a different doctor or place for special MEPS

care, does (CHILD) need approval or a referral?
Page 34 [ Series 1, No. 40

Glossary

CAHPS—Consumer Assessment of

Health Plans (sponsored by the Agency

for Healthcare Research and Quality).

CSHCN Screener—Children with

Special Healthcare Needs Screener

(Bethell, Read, et al., 2002).

CWF-PDS—Commonwealth Fund

Pediatric Developmental Services

Survey.

CWF-SPYC—Commonwealth Fund

Survey of Parents with Young Children

CPRQ—California Physician Referral

Questionnaire.

ECLS—Early Childhood Longitudinal

Study (conducted by the National Center

for Education Statistics).

LACHS—Los Angeles County Health

Survey (conducted by the Los Angeles

County Department of Health Services).

MEPS—Medical Expenditure Panel

Survey (conducted by the Agency for

Healthcare Research and Quality).

MHI5—Mental Health Index (Stewart

and Ware, 1992).

NHIS—National Health Interview

Survey (conducted by the National

Center for Health Statistics).

NS-CSHCN—National Survey of

Children with Special Health Care

Needs (conducted by the National

Center for Health Statistics).

PEDS—Parent’s Evaluation of

Developmental Status (Glascoe, 1998).

PHDS—Promoting Healthy

Development Survey (Bethell, Peck, and

Schor, 2001).

PHDS+—Promoting Healthy

Development Survey PLUS (conducted

by the Foundation for Accountability).

PSID-CD—Panel Study of Income

Dynamics–Child Development

Supplement (conducted by the Institute

for Social Research, University of

Michigan).

Bibliography

Bethell C, Read D, Stein REK,

Blumberg SJ, Wells N, Newacheck PW.

Identifying children with special health

care needs: development and evaluation

of a short screening tool. Ambulatory

Pediatrics. 2:38–48. 2002.

Bethell C, Peck C, Schor E. Assessing

health system provision of well-child

care: The promoting healthy

development survey. Pediatrics

107:1084–94. 2001.

Glascoe FP. Parents’ evaluation of

developmental status: a method for

detecting and addressing developmental

and behavioral problems in children.

Nashville, TN: Ellsworth & Vandermeer

Press Ltd. 1997.

Stewart AL, Ware JE Jr. Measuring

functioning and well-being: The medical

outcomes study approach. RAND

Corporation. Durham, North Carolina:

Duke University Press. 373–403. 1992.
Series

1, No. 40[ Page 35

Appendix III
Page 36 [ Series 1, No. 40
Series 1, No. 40 [ Page 37
Page 38 [ Series 1, No. 40
Series 1, No. 40 [ Page 39
Page 40 [ Series 1, No. 40
Series 1, No. 40 [ Page 41
Page 42 [ Series 1, No. 40
Series 1, No. 40 [ Page 43
Page 44 [ Series 1, No. 40
Series 1, No. 40 [ Page 45
Page 46 [ Series 1, No. 40
Series 1, No. 40 [ Page 47
Page 48 [ Series 1, No. 40
Series 1, No. 40 [ Page 49
Page 50 [ Series 1, No. 40
Series 1, No. 40 [ Page 51
Page 52 [ Series 1, No. 40
Series 1, No. 40 [ Page 53
Page 54 [ Series 1, No. 40
Series 1, No. 40 [ Page 55
Page 56 [ Series 1, No. 40
Series 1, No. 40 [ Page 57
Page 58 [ Series 1, No. 40
Series 1, No. 40 [ Page 59
Page 60 [ Series 1, No. 40
Series 1, No. 40 [ Page 61
Page 62 [ Series 1, No. 40
Series 1, No. 40 [ Page 63
Page 64 [ Series 1, No. 40
Series 1, No. 40 [ Page 65
Page 66 [ Series 1, No. 40
Series 1, No. 40 [ Page 67
Page 68 [ Series 1, No. 40
Series 1, No. 40 [ Page 69
Page 70 [ Series 1, No. 40
Series 1, No. 40 [ Page 71
Page 72 [ Series 1, No. 40
Series 1, No. 40 [ Page 73
Page 74 [ Series 1, No. 40
Series 1, No. 40 [ Page 75
Page 76 [ Series 1, No. 40
Series 1, No. 40 [ Page 77
Page 78 [ Series 1, No. 40
Series 1, No. 40 [ Page 79
Page 80 [ Series 1, No. 40
Series 1, No. 40 [ Page 81
Page 82 [ Series 1, No. 40
Series 1, No. 40 [ Page 83
Page 84 [ Series 1, No. 40
Series 1, No. 40 [ Page 85
Page 86 [ Series 1, No. 40
Series 1, No. 40 [ Page 87
Page 88 [ Series 1, No. 40
Series 1, No. 40 [ Page 89
Page 90 [ Series 1, No. 40
Series 1, No. 40 [ Page 91

Appendix IV

Advance Letter

FROM THE DIRECTOR

NATIONAL CENTER FOR HEALTH STATISTICS

As part of an important study conducted by the United States Department of Health and Human Services (DHHS), in collaboration

with the American Academy of Pediatrics (AAP), parents nationwide are being interviewed over the telephone about the health of

young children and their experiences with doctors. The interview includes questions about vaccinations, doctor’s visits, and early

childhood experiences. Within the next few weeks, your household may be called to take part in this study.

We are relying on your help to make this study a success. Although participation is completely voluntary and there is no penalty

for not answering any question, we hope you will agree to participate. The information we are gathering will help shape health

care policy in the years ahead.

Your telephone number was selected at random using scientific methods and your address was obtained through the telephone

directory. If no children under 3 years of age are living in your household, this survey will take only a few minutes. For

households with children under 3 years of age, most will finish within 20–25 minutes. A few may take longer. You may skip

questions you do not want to answer or end the interview at any time.

This survey is authorized by Section 306 and 2102(a)(7) of the Public Health Service Act. The information you provide is used for

research purposes only and will be held in strict confidence in accordance with Section 308(d) of the Public Health Service Act

[42 U.S. Code 242m(d)]. By law, the National Center for Health Statistics (NCHS), DHHS, and its contractors must keep all of

your information confidential. Participation is voluntary and will in no way affect any benefits you may receive now or in the

future.

If you have any questions about the study, please call our toll-free number, 1–877-587–1345 to learn more about the study. This

study has been approved by the NCHS Institutional Review Board. If you have questions about your rights as a study participant,

you may call Margot Palmer, Institutional Review Board chairman, toll-free at 1–800-223–8118.

We appreciate your taking the time to talk to us. Thank you for your assistance.

Sincerely,

Edward J. Sondik, Ph.D.

Director

It is important that the information we collect is as accurate as possible. If you have children between the ages of 12 months

and 3 years old living in your household, we would like you to use the vaccination or shot record for each child during the

interview. Please take a few minutes now to be sure you know where these records are located. Thank you.

If you prefer to contact us using a TTY, please call the AT&T Relay Service at 1–800-682–8786 and request that

1–800-247–1970 be called.
Page 92 [ Series 1, No. 40

Appendix V

Disposition Code

Frequencies and Response

Rate Calculations

Table 1. Frequencies of disposition codes for total combined sample

Disposition Percent of

Disposition code by name category Frequency total

No contact .............................................. UH 13,197 7.23%

3+ Fax/modem prior to any contact ............................... Z 8,055 4.41%

2+ Temporarily not in service ................................... Z 2,135 1.17%

Nonworking number ........................................ Z 21,651 11.86%

Number changed .......................................... Z 1,417 0.78%

Answering machine- known HH ................................. UO 166 0.09%

Answering machine- not HH ................................... Z 2,027 1.11%

Answering machine- HH unknown................................ UH 2,911 1.59%

Answering service- not HH .................................... Z 61 0.03%

Answering service- HH unknown ................................ UH 29 0.02%

Spanish- HH unknown ....................................... UH 35 0.02%

Other language- HH unknown .................................. UH 63 0.03%

Physical/mental impairment-HH unknown ........................... UH 12 0.01%

Callback at introduction- HH status unknown ......................... UH 376 0.21%

Appointment at introduction- HH unknown ........................... UH 13 0.01%

Broken appointment at introduction- HH unknown ...................... UH 232 0.13%

Hangup during introduction .................................... UH 1,205 0.66%

Refusal at introduction ....................................... UH 4,538 2.49%

Callback- HH............................................. UO 675 0.37%

Appointment- HH .......................................... UO 80 0.04%

Broken appointment- HH ..................................... UO 201 0.11%

Refusal- HH ............................................. UO 2,530 1.39%

Callback- partial NIS complete .................................. R 17 0.01%

Appointment- partial NIS complete ............................... R 10 0.01%

Broken appointment- NIS partial complete........................... R 7 0.00%

Break off- NIS partial complete.................................. R 246 0.13%

Break off- NIS partial complete, minority eligibility unknown ................ UO 216 0.12%

Not residential ............................................ Z 14,938 8.18%

Refusal/break off- age eligibility unknown ........................... UO 160 0.09%

Refusal/break off prior to A6Q03................................. R 185 0.10%

Callback prior to A6Q03 ...................................... R 38 0.02%

Appointment prior to A6Q03 ................................... R 11 0.01%

Break off- partial SLAITS complete ............................... P 3 0.00%

Eligible respondent- language barrier .............................. Y 28 0.02%

No children in range ........................................ X 65,664 35.97%

No child sampled .......................................... X 1,406 0.77%

Completed interview ........................................ I 1,939 1.06%

Converted interview ........................................ I 126 0.07%

GENESYS-resolved numbers .................................. Z 35,969 19.70%

Total .................................................. 182,572 100.00%

HH is household.
Series 1, No. 40 [ Page 93

Table 2. Response rate calculations for total combined sample

Frequency or Code or

calculated rate formula

Summary of disposition categories

Completes ..............................................

Partial completes ..........................................

Unknown HH.............................................

HH, eligibility unknown.......................................

Screened, eligible, refused ....................................

Screened, ineligible.........................................

Screened, eligible, language barrier...............................

Out of scope .............................................

Total ..................................................

Calculation of response rates

Interview completion rate .....................................

Screener completion rate .....................................

(Age for main sample) .......................................

Resolution rate ...........................................

CASRO rate .............................................

Summary of disposition categories

for calculation of alternative

screener completion rate

Completes ..............................................

Partial completes ..........................................

Unknown HH.............................................

HH, eligibility unknown ......................................

Screened, eligible, refused ....................................

Screened, ineligible.........................................

Screened, eligible, language barrier...............................

Out of scope .............................................

Total ..................................................

Calculation of response rates using

alternative screener completion rate

Interview Completion Rate ....................................

Screener completion rate .....................................

(Post-NIS for main sample) ...................................

Resolution rate ...........................................

CASRO Rate.............................................

2,065 C

3 P

22,611 UH

4,028 UO

514 R

67,070 X

28 Y

86,253 Z

182,572

79.23% (C+P) / (C+P+R+Y)

94.54% (C+P+R+X+Y) /

(C+P+R+X+Y+UO)

87.62% (C+P+R+X+Y+Z+UO) /

(C+P+R+X+Y+Z+UO+UH)

65.63% (ICR)(SCR)(RR)

2,065 C

3 P

22,611 UH

4,210 UO

332 R

67,070 X

28 Y

86,253 Z

182,572

85.17% (C+P) / (C+P+R+Y)

94.29% (C+P+R+X+Y) /

(C+P+R+X+Y+UO)

87.62% (C+P+R+X+Y+Z+UO) /

(C+P+R+X+Y+Z+UO+UH)

70.37% (ICR)(SCR)(RR)

HH is household.

CASRO is Council of American Survey Research Organizations.
Page 94 [ Series 1, No. 40

Table 3. Frequencies of disposition codes for main sample

Disposition Percent of

Disposition code by name category Frequency total

No contact .............................................. UH 4,884 6.88%

3+ Fax/modem prior to any contact ............................... Z 3,110 4.38%

2+ Temporarily not in service ................................... Z 947 1.33%

Nonworking number ........................................ Z 9,331 13.14%

Number changed .......................................... Z 531 0.75%

Answering machine- known HH ................................. UO 63 0.09%

Answering Machine- not HH ................................... Z 750 1.06%

Answering Machine- HH unknown................................ UH 1,102 1.55%

Answering Service- not HH .................................... Z 22 0.03%

Answering Service- HH unknown ................................ UH 11 0.02%

Spanish- HH unknown ....................................... UH 13 0.02%

Other language- HH unknown .................................. UH 22 0.03%

Physical/mental impairment-HH unknown ........................... UH 7 0.01%

Callback at introduction- HH status unknown ......................... UH 130 0.18%

Appointment at introducton- HH status unknown ....................... UH 5 0.01%

Broken appointment at introduction- HH unknown ...................... UH 78 0.11%

Hangup during introduction .................................... UH 457 0.64%

Refusal at introduction ....................................... UH 1,664 2.34%

Callback- HH............................................. UO 246 0.35%

Appointment- HH .......................................... UO 31 0.04%

Broken appointment- HH ..................................... UO 65 0.09%

Refusal- HH ............................................. UO 962 1.35%

Callback- NIS Partial complete .................................. R 13 0.02%

Appointment- NIS partial complete ............................... R 5 0.01%

Broken appointment- NIS partial complete........................... R 3 0.00%

Break off- NIS partial complete.................................. R 161 0.23%

Not Residential ........................................... Z 5,790 8.15%

Refusal/break off- age eligibility unknown ........................... UO 91 0.13%

Refusal/break off prior to A6Q03................................. R 121 0.17%

Callback prior to A6Q03 ...................................... R 22 0.03%

Appointment prior to A6Q03 ................................... R 6 0.01%

Break off- partial SLAITS complete ............................... P 1 0.00%

Eligible respondent- language barrier .............................. Y 23 0.03%

No children in range ........................................ X 24,837 34.98%

Completed interview ........................................ I 1,134 1.60%

Converted interview ........................................ I 73 0.10%

GENESYS-resolved numbers .................................. Z 14,298 20.14%

Total .................................................. 71,009 100.00%

HH is household.
Series 1, No. 40 [ Page 95

Table 4. Response rate calculations for main sample

Frequency or Code or

calculated rate formula

Summary of disposition categories

Completes ..............................................

Partial completes ..........................................

Unknown HH.............................................

HH, eligibility unknown.......................................

Screened, eligible, refused ....................................

Screened, ineligible.........................................

Screened, eligible, language barrier...............................

Out of scope ............................................

Total ..................................................

Calculation of response rates

Interview completion rate .....................................

Screener completion rate (Age) .................................

Resolution rate ...........................................

CASRO rate .............................................

Summary of disposition categories

for calculation of

alternative screener completion rate

Completes ..............................................

Partial completes ..........................................

Unknown HH.............................................

HH, eligibility unknown.......................................

Screened, eligible, refused ....................................

Screened, ineligible.........................................

Screened, eligible, language barrier...............................

Out of scope .............................................

Total ..................................................

Calculation of response rates using

alternative screener completion rate

Interview completion rate .....................................

Screener completion rate (Post-NIS) ..............................

Resolution rate ...........................................

CASRO rate .............................................

1,207 C

1 P

8,373 UH

1,458 UO

331 R

24,837 X

23 Y

34,779 Z

71,009

77.34% (C+P) / (C+P+R+Y)

94.77% (C+P+R+X+Y) /

(C+P+R+X+Y+UO)

88.21% (C+P+R+X+Y+Z+UO) /

(C+P+R+X+Y+Z+UO+UH)

64.65% (ICR)(SCR)(RR)

1,207 C

1 P

8,373 UH

1,640 UO

149 R

24,837 X

23 Y

34,779 Z

71,009

87.53% (C+P) / (C+P+R+Y)

94.11% (C+P+R+X+Y) /

(C+P+R+X+Y+UO)

88.21% (C+P+R+X+Y+Z+UO) /

(C+P+R+X+Y+Z+UO+UH)

72.66% (ICR)(SCR)(RR)

HH is household.

CASRO is Council of American Survey Research Organizations.
Page 96 [ Series 1, No. 40

Table 5. Frequencies of disposition codes for oversample

Disposition Percent of

Disposition code by name category Frequency total

No contact .............................................. UH 8,313 7.45%

3+ Fax/modem prior to any contact ............................... Z 4,945 4.43%

2+ temporarily not in service ................................... Z 1,188 1.06%

Nonworking number ........................................ Z 12,320 11.04%

Number changed .......................................... Z 886 0.79%

Answering machine- known HH ................................. UO 103 0.09%

Answering machine- not HH ................................... Z 1,277 1.14%

Answering machine- HH unknown................................ UH 1,809 1.62%

Answering service- not HH .................................... Z 39 0.03%

Answering service- HH unknown ................................ UH 18 0.02%

Spanish- HH unknown ....................................... UH 22 0.02%

Other language- HH unknown .................................. UH 41 0.04%

Physical/mental impairment-HH unknown ........................... UH 5 0.00%

Callback at introduction- HH status unknown ......................... UH 246 0.22%

Appointment at introduction- HH unknown ........................... UH 8 0.01%

Broken appointment at introduction- HH unknown ...................... UH 154 0.14%

Hangup during introduction .................................... UH 748 0.67%

Refusal at introduction ....................................... UH 2,874 2.58%

Callback- HH............................................. UO 429 0.38%

Appointment- HH .......................................... UO 49 0.04%

Broken appointment- HH ..................................... UO 136 0.12%

Refusal- HH ............................................. UO 1,568 1.41%

Callback- NIS partial complete, eligible............................. R 4 0.00%

Appointment- NIS partial complete, eligible .......................... R 5 0.00%

Broken appointment- NIS partial complete, eligible ..................... R 4 0.00%

Break off- NIS partial complete, eligible ............................ R 85 0.08%

Break off- NIS partial complete, minority eligibility unknown ................ UO 216 0.19%

Not Residential ........................................... Z 9,148 8.20%

Refusal/break off- age eligibility unknown ........................... UO 69 0.06%

Refusal/break off prior to A6Q03................................. R 64 0.06%

Callback prior to A6Q03 ...................................... R 16 0.01%

Appointment prior to A6Q03 ................................... R 5 0.00%

Break off- partial SLAITS complete ............................... P 2 0.00%

Eligible respondent - language barrier ............................. Y 5 0.00%

No children in range ........................................ X 40,827 36.60%

Child not sampled.......................................... X 1,406 1.26%

Completed interview ........................................ I 805 0.72%

Converted interview ........................................ I 53 0.05%

GENESYS-resolved numbers .................................. Z 21,671 19.42%

Total .................................................. 111,563 100.00%

HH is household.
Series 1, No. 40 [ Page 97

Table 6. Response rate calculations for oversample

Frequency or Code or

calculated rate formula

Summary of disposition categories

Completes ..............................................

Partial completes ..........................................

Unknown HH.............................................

HH, eligibility unknown.......................................

Screened, eligible, refused ....................................

Screened, ineligible.........................................

Screened, eligible, language barrier...............................

Out of scope .............................................

Total ..................................................

Calculation of response rates

Interview completion rate .....................................

Screener completion rate .....................................

Resolution rate ...........................................

CASRO rate .............................................

858 C

2 P

14,238 UH

2,570 UO

183 R

42,233 X

5 Y

51,474 Z

111,563

82.06% (C+P) / (C+P+R+Y)

94.39% (C+P+R+X+Y) /

(C+P+R+X+Y+UO)

87.24% (C+P+R+X+Y+Z+UO) /

(C+P+R+X+Y+Z+UO+UH)

67.58% (ICR)(SCR)(RR)

HH is household.

CASRO is Council of American Survey Research Organizations.
Vital and Health Statistics

series descriptions

SERIES 1.	 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. 

SERIES 2.	 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. 

SERIES 3.	 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. 

SERIES 4.	 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. 

SERIES 5.	 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. 

SERIES 6.	 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. 

SERIES 10.	 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. 

SERIES 11.	 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. 

SERIES 12.	 Data From the Institutionalized Population Surveys— 

Discontinued in 1975. Reports from these surveys are 

included in Series 13. 

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 longterm 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,

Divorce, and Induced Terminations of Pregnancy— 

These include advance reports of births, deaths, marriages, 

and divorces based on final data from the National Vital 

Statistics System that were published as supplements to the 

Monthly Vital Statistics Report (MVSR). These reports provide 

highlights and summaries of detailed data subsequently 

published in Vital Statistics of the United States. Other 

supplements to the MVSR 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: 

Data Dissemination Branch


National Center for Health Statistics


Centers for Disease Control and Prevention


6525 Belcrest Road, Room 1064


Hyattsville, MD 20782-2003


(301) 458–4636


E-mail: nchsquery@cdc.gov


Internet: www.cdc.gov/nchs