2014 National Youth Tobacco Survey

Methodology Report

For questions about this report, please email Sean Hu at shu@cdc.gov

Prepared for Centers for Disease Control and Prevention

Prepared by ICF International, Rockville, Maryland

Centers for Disease Control and Prevention

Office on Smoking and Health

Atlanta, GA

September 2015

Recommended Citation: Office on Smoking and Health. 2014 National Youth Tobacco Survey: 

Methodology Report. Atlanta, GA: U.S. Department of Health and Human Services, Centers for 

Disease Control and Prevention, National Center for Chronic Disease Prevention and Health 

Promotion, Office on Smoking and Health, 2015.

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Methodology Report: 2014 National Youth Tobacco Survey

Table of Contents- i

TABLE OF CONTENTS

Chapter 1—NYTS Sampling Design........................................................................................ 1

1.1 Overview of the National Youth Tobacco Survey (NYTS) ............................................... 1

1.2 Overview of the 2014 NYTS Methodology ...................................................................... 1

Chapter 2—NYTS Sampling Methods..................................................................................... 3

2.1 Overview ........................................................................................................................ 3

2.2 Stratification and Linking ................................................................................................ 7

2.3 Sampling Methods.........................................................................................................15

Chapter 3—NYTS Data Collection..........................................................................................20

3.1 Survey Instrument .........................................................................................................20

3.2 Recruitment Procedures................................................................................................20

3.3 Survey Administration....................................................................................................20

3.4 Participation Rates ........................................................................................................22

Chapter 4—Weighting of NYTS Response Data ...................................................................23

4.1 Overview .......................................................................................................................23

4.2 Sampling Weights .........................................................................................................23

4.3 Nonresponse Adjustments.............................................................................................26

4.4 Weight Trimming ...........................................................................................................28

4.5 Poststratification to National Student Population Estimates ...........................................29

4.6 Analysis Strata and Variance Estimation .......................................................................34

Appendices

A. Questionnaire

B. Student Weight Detail

C. Common Core of Data Race/Ethnicity Definitions

List of Exhibits and Figure

Exhibit 2-1: Key Sampling Design Features............................................................................ 6

Exhibit 2-2: Stratum Definition and PSU Allocation to Strata................................................... 9

Figure 2-1: Linked School Construction and Grade Sampling for High Schools.....................10

Exhibit 2-3: Historical Summary of NYTS Participation Rates................................................11

Exhibit 2-4: Planned Sample Sizes for the 2014 NYTS..........................................................14

Exhibit 3-1: Sample Yields for Non-Hispanic Black and Hispanic Students by School Level..22

Exhibit 4-1: Medium and Large School Nonresponse ..........................................................275
Methodology Report: 2014 National Youth Tobacco Survey

Table of Contents- ii

Exhibit 4-2: Poststratification Adjustments .............................................................................28

Exhibit 4-3: Sampling and Analysis Stratum Coding Schemes.............................................353

Exhibit 4-4a: Current Use Estimates for Selected Tobacco Products for High School Students 

(Standard Errors in Parentheses) .......................................................................................353

Exhibit 4-4b: Current Use Estimates for Selected Tobacco Products for Middle School 

Students (Standard Errors in Parentheses) .........................................................................364
Methodology Report: 2014 National Youth Tobacco Survey

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CHAPTER 1—NYTS SAMPLING DESIGN

1.1 Overview of the National Youth Tobacco Survey (NYTS)

In conjunction with the State Youth Tobacco Survey (YTS), the National Youth Tobacco Survey 

(NYTS) was developed to provide the data necessary to support the design, implementation, and 

evaluation of state and national tobacco prevention and control programs (TCPs).1,2In addition, 

NYTS data supplement other existing surveys, such as the Youth Risk Behavior Surveillance 

System (YRBSS), by providing more comprehensive data of tobacco-related indicators for both 

middle school (grades 6–8) and high school (grades 9–12) students. Tobacco-related indicators 

included in the NYTS include: tobacco use (e.g., bidis, cigarettes, cigars, kreteks, tobacco pipes, 

smokeless tobacco, snus, dissolvable tobacco products, hookahs, and electronic cigarettes); 

exposure to secondhand smoke; smoking cessation; school curriculum; minors’ ability to purchase 

or obtain tobacco products; and, knowledge and attitudes about tobacco and familiarity with protobacco and anti-tobacco media messages. NYTS data also serve as essential benchmarks against 

which TCPs can assess the extent of youth tobacco use. The NYTS provides multiple measures 

and data for six of the 20 tobacco-related Healthy People 2020 objectives (USDHHS, 2010): TU2, TU-3, TU-7, TU-11, TU-18 and TU-19.

First conducted during fall 1999 and again during spring 2000, 2002, 2004, 2006, 2009, 2011, 

2012, 2013 and 2014, the NYTS provides data that are representative of all middle school and high 

school students in the 50 U.S. States and the District of Columbia. Beginning in 2011, the Centers 

for Disease Control and Prevention (CDC) and the Food and Drug Administration (FDA) have 

collaborated to annually administer the NYTS.

1.2 Overview of the 2014 NYTS Methodology

The 2014 NYTS employed a stratified, three-stage cluster sample design to produce a nationally 

representative sample of middle school and high school students in the United States. NonHispanic black students were oversampled. Sampling procedures were probabilistic and conducted 

without replacement at all stages, and entailed selection of: 1) Primary Sampling Units (PSUs)

(defined as a county, or a group of small counties, or part of a very large county) within each 

created stratum; 2) Secondary Sampling Units (SSUs), (defined as schools or linked schools) 

within each selected PSU; and 3) students within each selected school. Participating students 

completed the survey via pencil and paper using a self-administered, scannable questionnaire 

booklet.

Participation in the NYTS was voluntary at both the school and student levels. At the student level, 

participation was anonymous. Schools used either passive or active permission forms at their 

 

1 Centers for Disease Control and Prevention. (CDC) (2014). Best Practices for comprehensive tobacco control 

programs-2014. Atlanta, GA: US Department of Health and Human Services, Public Health Service, CDC.

2 MacDonald, G., Starr, G., Schooley, M., Yee, S. L., Klimowski. K., Turner, K. (2001). Introduction to program 

evaluation for comprehensive tobacco control programs. Atlanta, GA: US Department of Health and Human 

Services, CDC.
Methodology Report: 2014 National Youth Tobacco Survey

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discretion to fulfill requirements of the No Child Left Behind Act, whereby parents must be 

provided with a means to opt out of their child’s participation.

The final sample consisted of 258 schools, of which 207 participated, yielding a school 

participation rate of 80.2%. A total of 22,007 student questionnaires were completed out of a 

sample of 24,084 students, yielding a student participation rate of 91.4%. The overall participation 

rate, defined as the product of the school-level and student-level participation rates, was 73.3%.

A weighting factor was applied to each student record to adjust for nonresponse and for varying 

probabilities of selection. Weights were adjusted to ensure that the weighted proportions of 

students in each grade matched national population proportions. 

The remainder of this report provides detailed information on the methodology used in the 2014 

NYTS sample selection (Chapter 2), data collection (Chapter 3), and weighting of student response 

data (Chapter 4).
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CHAPTER 2—NYTS SAMPLING METHODS

2.1 Overview

The objective of the NYTS sampling design was to support estimation of tobacco-related

knowledge, attitudes, and behaviors in a national population of public and private school students 

enrolled in grades 6 through 12 in the United States. More specifically, the study was designed to 

produce national estimates at a 95% confidence level with a margin of error of 5% by school level 

(middle school and high school), by grade (6, 7, 8, 9, 10, 11, and 12), by sex (male and female), 

and by race/ethnicity (non-Hispanic white, non-Hispanic black, and Hispanic). Additional 

estimates were also supported for subgroups defined by grade, by sex, and by race/ethnicity, each 

within school level domains; however, precision levels will vary considerably according to 

differences in subpopulation sizes.

The universe for the study consisted of all public and private school students enrolled in regular 

middle schools and high schools in grades 6 through 12 in the 50 U.S. States and the District of 

Columbia. Alternative schools, special education schools, Department of Defense operated 

schools, vocational schools that serve only pull-out populations, and students enrolled in regular 

schools unable to complete the questionnaire without special assistance, were excluded. 

The 2014 NYTS is a continuation of the NYTS cycles that took place in 1999, 2000, 2002, 2004, 

2006, 2009, 2011, 2012 and 2013. The NYTS employs a repeat cross-sectional design to develop 

national estimates of tobacco use behaviors and exposure to pro- and antitobacco influences among 

students enrolled in grades 6–12. The general sampling design framework used for the 2013 NYTS 

was also employed for the 2014 NYTS. 

2.1.1 Oversampling of Racial/Ethnic Minorities

To facilitate accurate prevalence estimates among racial/ethnic minority groups, prior cycles of 

the NYTS have employed multiple strategies to increase the number of non-Hispanic black and 

Hispanic students included in the sample. These approaches have included over-sampling PSUs in 

high racial/ethnic minority strata, the use of a weighted measure of size (MOS), and double class 

selection in large schools that contain a sufficient proportion of minority students.

The design development process examines parameters such as thresholds for double class selection 

and PSU allocation to strata, to balance the dual goals of overall precision and minority group 

targets. 

The sampling design balances increasing yields for minority students with overall precision as 

oversampling leads to larger variances for overall estimates. As described below, the only 

oversampling that remains in the more efficient design for the 2014 NYTS is double class 

sampling. This method has been shown to reduce design effects for survey estimates. The design 

effect, defined as the variance of actual survey estimates divided by the variance of a simple 

random sample of the same size, is a common useful measure of the precision of survey estimates.

A weighted measure of size (MOS) was previously used to increase the probability of selection 

of high racial/ethnic minority PSUs and schools using a Probability Proportional to Size (PPS) 

sampling design. The effectiveness of a weighted MOS in achieving oversampling is dependent 
Methodology Report: 2014 National Youth Tobacco Survey

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upon the distributions of non-Hispanic black and Hispanic students in schools. The need for a 

weighted MOS is predicated on a relatively low prevalence of minority students in the 

population; however, this premise has become less tenable with the increase of nonwhite 

students in the population overall, and specifically, Hispanic students. The need for 

oversampling Hispanic students has been gradually reduced with the increasing numbers of 

Hispanics among the student population. As seen below, some degree of oversampling nonHispanic black students remains in the sampling design.

In 1990, the contactor, ICF (formerly Macro International Inc.), conducted the first in a series of 

simulation studies to investigate the impact of various weighting functions on the numbers and 

percentages of racial/ethnic minority students reached in YRBS.3 Sampling strategies based on 

this work were incorporated into the NYTS, and these simulations have been updated with each 

cycle of the NYTS to ensure that the minimum amount of weighting in the MOS is being used, 

while still achieving adequate representation of non-Hispanic black and Hispanic students. When 

the possibility of using an unweighted measure of enrollment size was investigated for the 2012 

NYTS, results demonstrated that adequate representation of non-Hispanic black and Hispanic 

students would be achieved through the use of an unweighted MOS. Thus, starting with the 2013 

NYTS and continuing for 2014 NYTS, student enrollment was used as the unweighted MOS, 

leading to improvements in the statistical efficiency of the design.

The MOS used in the 2014 NYTS sampling design no longer oversampled schools with heavier 

minority concentrations directly. In addition, the allocation to strata was proportional so the second 

oversampling approach was also no longer in effect. Nevertheless, double class selection was still 

implemented in the 2014 NYTS sampling.

In previous NYTS cycles, schools with high racial/ethnic populations were subject to double class 

selection. More specifically, two classes per grade were selected in these schools, compared to one 

class per grade in other schools, to increase the number of racial/ethnic minority students sampled. 

In the 2014 NYTS, double class selection was used only in large schools that had greater than 3% 

non-Hispanic black student enrollment. The threshold was developed, and updated, to generate the 

necessary numbers of participating non-Hispanic black students to ensure estimation precision for 

this subgroup.

2.1.2 Frame Construction

The frame was constructed from separate sources obtained from the National Center for Education 

Statistics (NCES) and from a commercial vendor, Market Data Retrieval Inc. (MDR Inc). The 

NCES files were the Common Core of Data (CCD) for public schools and Private School Survey 

(PSS) for private schools. In addition, the frame incorporated data from the MDR dataset. 

The reason for moving to a frame built from multiple data sources is to increase the coverage of 

schools nationally. This dual-source frame build method was implemented for the 2014 NYTS 

 

3 Errecart, M. T. (1990, October 5). Issues in Sampling African-Americans and Hispanics in School-Based Surveys.

Atlanta, GA: Centers for Disease Control.
Methodology Report: 2014 National Youth Tobacco Survey

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survey for the first time4. Including schools sourced from the two NCES files resulted in a 

coverage increase among all public and non-public high schools of 23%. There was a 15.5% 

increase of coverage among public schools and a 46% increase in coverage among non-public high 

schools. 

2.1.3 Sampling Stages and Measure of Size

The three-stage cluster sample was stratified by racial/ethnic composition and urban versus 

nonurban status at the first (primary) stage. PSUs were defined as a county, a group of smaller 

counties, or a portion of a very large county. PSUs were classified as “urban” if they are in one of 

the 54 largest metropolitan statistical areas (MSAs) in the U.S using 2012 American Community 

Survey (ACS) data from the US Census Bureau. Otherwise, they were classified as “non-urban.”

The 16 primary strata are defined in Exhibit 2-2. Additionally, implicit stratification was imposed 

by geography by sorting the PSU frame by State and by 5-digit ZIP Code (within State). Within 

each stratum, a PSU was randomly sampled without replacement at the first stage.

In subsequent sampling stages, a probabilistic selection of schools and students was made from 

the sample PSUs. It may be helpful to stress one feature of the 2014 NYTS sample which, as in 

the 2012 NYTS, was designed to balance the student yields for the two school levels—middle 

schools and high schools. As high schools have more grades, 4 grades versus 3 grades for middle 

schools, and therefore more students, fewer sample schools were selected at the high school level 

than at the middle school level. This was implemented by subsampling PSUs for high schools—

for large schools as well as for medium and small schools. For medium and small schools, we 

subsampled fewer PSUs for high school than for middle school sampling.

The sampling stages may be summarized as follows, with additional details provided in Section 2.2:

 Selection of PSUs: Ninety-three PSUs were selected from 16 strata, with probability 

proportional to the total number of eligible students enrolled in all eligible schools 

located within a PSU.

 Selection of Schools: At the second sampling stage, a total of 170 large schools, or 

second-stage units (SSUs) were selected from the sample PSUs. While one large middle 

school was selected from each of the 93 sample PSUs, one large high school was selected 

from each of 77 subsample PSUs (170 = 93 + 77). An additional 20 medium schools and 

30 small schools were selected from subsample PSUs, for a total of 220 sample SSUs 

(220= 170+30+20). The PSU subsample was drawn as a simple random sample, and the 

schools were drawn with probability proportional to the total number of eligible students 

enrolled in a school.

 Selection of Students: Students were selected via whole classes, whereby all students 

enrolled in any one selected class were by default chosen for participation. Classes were 

selected from course schedules provided by each school that agreed to participate. 

Schedules were constructed such that all eligible students were represented one time only.

 

4 Redesigning National School Surveys: Coverage and Stratification Improvement using Multiple Datasets. William 

Robb, Kate Flint, Alice Roberts, Ronaldo Iachan - ICF International, FEDCASIC March 2014
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Schools were stratified into large, medium and small schools based on their ability to support two, 

one, or less than one class selection per grade. In large schools, an average of 1.46 classes were 

selected per grade by selecting two classes per grade in 46% of selected large schools and one class 

per grade in the remaining schools. The double class sampling took place in schools with nonHispanic black enrollments over the established 3% threshold. Specifically, double class sampling 

took place by design in 78 of the 170 sample large schools, or 45.8% of these schools.

The sampling approach utilized PPS sampling methods. In PPS sampling, when the MOS is 

defined as the count of final-stage sampling units, and a fixed number of units are selected in the 

final stage, the result is an equal probability of selection for all members of the universe. For the 

NYTS, we approximate these conditions, and thus obtain a roughly self-weighting sample.

The MOS also was used to compute stratum sizes and PSU sizes. Assigning an aggregate measure 

of size to PSU, the sample allocates the PSU sample in proportion to the student population. 

Exhibit 2-1 presents a high-level summary of the key sampling design features that will be 

described in detail in the next sections.

EXHIBIT 2-1: KEY SAMPLING DESIGN FEATURES

Sampling 

Stage

Sampling 

Units Sample Size (Approximate) Stratification Measure of Size

1 PSUs 

(Counties or 

groups of 

counties)

93 Counties or groups of 

counties

Urban vs. nonurban

(2 strata);

Minority concentration

(8 strata)

Aggregate school size in 

target grades

2 SSUs 

(Schools)

220 SSU (school) selections: 

170 large schools, 20 medium 

schools and 30 small schools

Small, medium and 

large;

High school vs. middle 

school

Eligible enrollment 

3 Classes/ 

students

1 or 2 classes per grade (2 

per grade in large, highminority schools)
Methodology Report: 2014 National Youth Tobacco Survey

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2.2 Stratification and Linking

This section describes the following steps that are necessary for the selection of the first- and 

second-stage samples of PSUs and schools: organizing counties into Primary Sampling Units; 

linking schools into SSUs; and the stratification and allocation methods at each of these stages.

2.2.1 Primary Sampling Unit (PSU)

Defining a PSU

In general, PSUs are geographic areas defined as counties or groupings of counties. In defining a 

PSU, several issues are considered:

1. Each PSU should be large enough to contain the requisite numbers of schools and 

students by grade, yet not so large as to be selected with near certainty.

2. Each PSU should be compact geographically so that field staff can go from school to 

school easily.

3. Recent data should be available to characterize each PSU.

4. Each PSU should contain at least four middle and five high schools.

Generally, counties were equivalent to PSUs with two exceptions: 1) low population counties are 

combined to provide sufficient numbers of schools and students; and 2) counties that are very large 

may be split to avoid becoming certainty or near-certainty PSUs. Certainty PSUs are those whose 

size is large enough to ensure selection with probability one (1.0) with a PPS sampling design that 

selects larger PSUs with larger probabilities. As certainty PSUs lead to inefficiencies in the design, 

they are split so that the new smaller units are no longer selected with a probability of one. Nearcertainty units are also split to build in a safety buffer in the PSU sizes. County population figures 

were aggregated from school enrollment data for the grades of interest.

The 2014 NYTS PSU definitions were based on the definitions developed in the coordinated 2011 

and 2013 YRBS-NYTS cycles, and also used in the 2012 NYTS cycle. The exact PSUs defined in 

2014 NYTS sampling frame were updated to ensure that all PSU met the criteria above. The frame 

had 1,268 PSUs, 529 of which were comprised of one single county. 

Stratification of PSUs

The PSUs were organized into 16 strata, based on urban/nonurban location (as defined above) and 

racial/ethnic minority enrollment of non-Hispanic blacks and Hispanics. In the traditional 

stratification used by the NYTS the classification of PSUs into the two racial/ethnic minority strata, 

non-Hispanic black and Hispanic, is based on the predominant minority in the PSU. This 

classification is coupled with the density distribution of non-Hispanic blacks and Hispanics to 

subdivide each of the four primary strata into four substrata, indexed by 1-4 according to this 

density. The determination of the substratum boundaries is described below.
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The approach involves the computation of optimum stratum boundaries using the cumulative 

square root of “f” method developed by Dalenius and Hodges.5 The boundaries or cutoffs change 

as the frequency distribution (“f”) for the racial groupings change from one survey cycle to the 

next. These rules are summarized below.

 If the PSU is within one of the 54 largest MSA in the U.S. it is classified as “urban,” 

otherwise it is classified as “nonurban.”

 If the percentage of Hispanic students in the PSU exceeded the percentage of nonHispanic black students, then the PSU is classified as Hispanic. Otherwise it is classified 

as non-Hispanic black.

 Hispanic urban and Hispanic nonurban PSUs were classified into four density groupings, 

depending upon the percentages of Hispanics in the PSU.

o For urban, High Hispanic PSU, the percentage cut points used to define the 

groups were 24, 40, and 60%.

o For nonurban, High Hispanic PSU, the percentage cut points used to define the 

groups were 24, 50, and 68%.

 Non-Hispanic Black urban and non-Hispanic black nonurban PSUs also were classified 

into four groupings, depending upon the percentages of non-Hispanic blacks in the PSU. 

o For urban non-Hispanic black PSUs, the percentage cut points used to define the 

groups were 26, 36, and 54%.

o For nonurban High non-Hispanic Black PSUs, the percentage cut points used to 

define the groups were 20, 36, and 58%.

 

5 Dalenius, T., & Hodges, J. L. (1959). Minimum Variance Stratification. Journal of American Statistical 

Association, 54, 88−101.
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Allocation of the PSU Sample

We designed and selected a sample of 93 PSUs that were allocated in proportion to student 

enrollment. Using simulations as in previous studies, we then made adjustments to the initial 

allocation to meet racial/ethnic minority targets. Specifically, the adjustments rounded fractional 

allocations, ensured that each stratum would have at least two sampled PSUs, and added balance 

to the distribution across strata.

Exhibit 2-2 presents the allocation of the PSU sample to strata. Compared to previous cycles, this 

allocation is closer to proportional, and therefore, more efficient statistically (i.e., it leads to smaller 

variances and tighter confidence intervals).

EXHIBIT 2-2: STRATUM DEFINITION AND PSU ALLOCATION TO STRATA

Predominant 

Minority Urban/Nonurban

Density 

Group 

Number

Stratum 

Code

Student 

Population

Number 

of 

Sample 

PSUs

NonHispanic 

Black

Urban 1 BU1 2,720,181 9

2 BU2 975,490 3

3 BU3 908,299 3

4 BU4 516,712 2

Nonurban 1 BR1 3,937,157 12

2 BR2 1,503,403 5

3 BR3 1,026,612 4

4 BR4 313,063 2

Hispanic Urban 1 HU1 3,530,556 11

2 HU2 2,429,442 7

3 HU3 1,865,988 5

4 HU4 2,106,242 7

Nonurban 1 HR1 4,427,215 14

2 HR2 1,284,402 4

3 HR3 988,655 3

4 HR4 523,491 2
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2.2.2 Schools

Linking into Second-stage Sampling Unit (SSU)

Schools were classified as “whole” for high 

schools if they have all high-school grades 9 

through 12, and whole for middle schools if they 

had all grades 6–8. Otherwise, they were 

considered a “fragment” school. Fragment 

schools formed component schools that were 

linked with other schools (fragment or whole) to 

form a linked school that has all four grades. This 

process is illustrated in Figure 2-1, where 

“Component School A” is linked with “Component School B,” to form a linked school. We linked 

schools before sampling using an algorithm developed for use in the national YRBS that links 

geographically proximate schools. Linked schools were treated as second-stage sampling units

(SSUs) with selection performed at the grade level, as described below.

Stratification

SSUs were stratified by school level (middle and high) and by size. Middle schools were those 

that contained any of grades 6 through 8, and high schools were those that contained any of grades 

9 through 12. Schools that contained a mix of high and middle school grades were split into two 

sampling units, or one for each level.

SSUs also were stratified by school size into large, medium, and small strata on the basis of their 

ability to support less than one, one, or two class selections per grade. Operationally, large SSUs 

contained at least 56 students at each grade level, medium SSUs contained between 28 and 55

students per grade, and small SSUs contained less than 28 students at any grade level.

2.2.3 Sample Sizes

The original specifications for NYTS sample sizes were not given in terms of student yields; rather, 

they were specified in terms of the precision of the resulting estimates. Thus, the NYTS was 

designed to produce prevalence estimates for tobacco products with a margin of error (MOE) of 

5% (± 5%) at a 95% level of precision. Estimates by grade, sex, and grade by sex meet this 

standard. The same standard is used for the estimates for racial/ethnic groups by school level.

The NYTS is designed to produce accurate estimation within a MOE of 5% at a 95% precision 

level for the following key subgroup estimates:

 Middle and high school (school level): middle school students in total (grades 6–8 

combined) and high school students in total (grades 9–12 combined)

 Grade: individual grades 6, 7, 8, 9, 10, 11, and 12

 Sex: males and females in total, by school level (male middle school students, female 

high school students), and by individual grade (6-grade males, 6-grade females)

 Race/Ethnicity: in total and by school level (e.g., Hispanic middle school students)

FIGURE 2-1: LINKED SCHOOL CONSTRUCTION AND 

GRADE SAMPLING FOR HIGH SCHOOLS

Component School B

(Whole)

Component School A

(Fragment)

Grade 9

Grade 10 Grade 10

Grade 11 Grade 11

Grade 12 Grade 12
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Over the past several cycles of NYTS, we have confirmed that sample sizes, and resulting student 

yields, were sufficient to achieve design goals in terms of precision. The 2014 NYTS design meets 

the precision targets, while adjusting sampling parameters to reflect changing demographics of the 

in-school population of middle and high school students. Following derivations similar to previous 

cycles, these precision requirements necessitate a minimum sample size of 10,000 participating 

students per school level. This minimum sample size ensures that estimates by race/ethnicity meet 

the required precision levels for each school level. The target sample sizes correspond to 

approximately 3,000 participating students per grade—more for middle-school than high-school 

grades—and so they also ensure the precision of estimates by individual grade (e.g., sex by grade 

subgroup estimates on the basis of about 1,500 students).

Recall that the 2014 NYTS sampling design aimed at balancing student yields by school level 

(middle and high school) by subsampling PSUs for the high-school sample. The premise is that 

each high school provides student samples for four grades while each middle school provides 

student samples for three grades.

Across the nine previous cycles of the NYTS, the school participation has averaged 86.5%, with a 

low of 75.4%. Student participation has averaged 90.5% with a low of 87.6%. Historical 

participation rates at both school and student levels are summarized in Exhibit 2.3.

In calculating the sample sizes for the 2014 NYTS, we made our approach more robust by 

assuming a conservative combined rate of 77%, which was slightly lower than the historical overall 

response rate of 78.3%. . This combined participation rate could arise, for example, from student 

participation rates of 90% and 85.5%, respectively.

EXHIBIT 2-3: HISTORICAL SUMMARY OF NYTS PARTICIPATION RATES

YEAR School Participation Student Participation Overall

1999 90.3% 93.2% 84.2%

2000 90.0% 93.4% 84.1%

2002 83.1% 90.6% 75.3%

2004 92.7% 87.9% 81.5%

2006 91.6% 87.6% 80.2%

2009 92.3% 91.9% 84.8%

2011 83.2% 88.0% 73.2%

2012 80.3% 91.7% 73.6%

2013 75.4% 90.7% 68.4%

Average over all 

cylces 86.5% 90.5% 78.3%

 
Methodology Report: 2014 National Youth Tobacco Survey

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Next, we develop sampling parameters that will lead to a total projected sample size in excess of 

21,000 participants, and more than 10,000 participants per level. The total sample size developed 

in Exhibit 2-4 is also translated into a total of 27,374 students selected from all sample schools 

when the calculations account for the response rates at the school and student levels discussed 

below.

The architecture described in Exhibit 2-4 balances the target sample sizes needed for the two key 

domains defined by middle school and high school levels. This balance is achieved by considering 

different target sample sizes per grade needed for high school and middle school grades, as 

typically, middle schools supply three grades and high schools supply four grades. That is the case 

in every SSU selected for the two levels, as each SSU offers a complete set of grades for the level

(i.e., every SSU selected for the MS level supplies three grades and every SSU selected for the HS 

level supplies four grades).

Schools were further classified by size based on grade-level enrollments; the definition of size 

strata is provided in Section 2.2.2. This ensures that a sampled school of a given size classification 

is able to support the student sample sizes given in Exhibit 2-4.

The NYTS sample size calculations are based on the following assumptions:

 The main structure of the sampling design will be consistent with the design used to draw 

the sample for prior cycles of the NYTS.

 The selection of a minimum of one SSU at the high school level and one SSU at the middle 

school level within each PSU. Some PSUs are selected to provide up to four extra schools. 

A PSU is a county, a group of contiguous counties, or a section of a county if too large. 

 SSUs with at least 56 students per grade are considered large, and those among the others 

with 28 students per grade are considered medium; otherwise, they are considered small.

 On average, each selected class includes 28 students (on the basis of historical averages).

 For SSUs classified as large, we sample double the amount of students in 46% of these 

schools, by sampling eight classes instead of four.

 A 77% overall response rate (based on historical averages) calculated as the product of 

the school and student response rate.

Based on these assumptions, 93 PSUs were selected as the basis for the sample. Next, we describe 

selection of schools or SSUs, recalling the definition of SSUs as “linked schools” created by 

combining actual schools so that each linked school unit has a complete set of grades for the level.

The linking of actual schools into SSUs means that the selected school sample size, 220 SSUs, 

corresponds to a larger number of schools, projected to fall between 235 and 245 actual schools 

using an average number of schools/SSU estimated from previous cycles.

Large middle school SSUs were selected from the 93 sample PSUs, one middle school per PSU 

for a total of 93 large middle schools. For the selection of large high school SSUs, 77 PSUs were 

subsampled from the 93 sample PSUs, with 1 large high school selected from each of the 77 

subsample PSUs. Therefore, a total of 170 large schools or SSUs were selected into the sample.
Methodology Report: 2014 National Youth Tobacco Survey

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Another subset of PSUs was independently subsampled to supply medium schools as follows. A 

subsample of 12 PSUs were selected for medium middle schools and a subsample of 8 PSUs were 

selected for medium high schools. For small schools, in addition, 13 PSUs were subsampled to 

supply high schools and 17 PSUs were subsampled to supply middle schools. In each subsample 

PSU, we selected one school of the specified level (MS, HS) and size (medium or small).

Exhibit 2-4 summarizes the designed sample sizes for each school type; i.e., the number of schools 

that were specified to be drawn along with the anticipated number of participating schools and 

students. Section 3.4 compares these projections to the actual sample yields.
Methodology Report: 2014 National Youth Tobacco Survey

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EXHIBIT 2-4: PLANNED SAMPLE SIZES FOR THE 2014 NYTS

School 

Level Size Number of SSUs

Sample Size Calculations Yields @ 

77% 

Overall 

Response 

Rate

Number of 

Schools 

Sampled

Number of 

Classes 

Per School

Number of 

Students

Per Class

Sample 

Students 

Prior to 

Attrition

Middle Large 93 Double 

Classes: 43 6 28 7,224 5,562

Single 

Classes: 50 3 28 4,200 3,234

Total 93 11,424 8,796

Medium 12 12 3 28 1,008 776

Small 17 17 2.8 11.2 470 362

Total Middle 122 122 12,902 9,935

High Large 77 Double 

Classes: 35

8 28 7,840 6,037

Single 

Classes: 42 4 28 4,704 3,622

Total 77 12,544 9,659

Medium 8 8 4 28 896 690

Small 13 13 3.8 18.1 1,032 794

Total High 98 98 14,472 11,143

Overall Large 170 170 23,968 18,455

Medium 20 20 1,904 1,466

Small 30 30 1,502 1,157

Total Overall 220 220 27,374 21,078

Exhibit 2-4 also highlights the double class sampling that took place in a subset of large schools.

As mentioned in Section 2.1.1, double classes were selected in those large schools with a sufficient 

proportion of non-Hispanic blacks (i.e., at least 3% black).

These schools were expected to yield approximately 21,078 students. The large projected sample 

size permits analysis by individual grade and by sex without any special considerations in the 

sampling plan. Design effects were assumed by the design to be relatively small for subgroups that 

cut across schools; therefore, sex group estimates will have better precision than other groups. 

Thus, the designed confidence intervals were ± 3%. 

The next paragraphs discuss how the design was balanced to achieve precise estimates for 

subgroups defined by school level, grade, sex and race/ethnicity.
Methodology Report: 2014 National Youth Tobacco Survey

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2.2.3.1 Middle School and High School Estimates

Estimates by school level are required to support separate analysis of students across middle school 

grades (6, 7, and 8) and high school grades (9, 10, 11, and 12). However, schools tend to vary in 

their grade structures, an inconsistency that compromises the ability to easily and efficiently link 

schools for sampling purposes in a manner that also uniformly divides students by grade. For 

example, 9th-grade students are served by both junior high schools with grades 7–9 and by high 

schools with grades 9–12. As a result, we have developed the school linking approach described in 

Section 2.2.2 that was applied independently for high schools and middle schools.

2.2.3.2 Grade Estimates

The designed sample sizes are approximately balanced for school-level and for grade-level 

groupings. By targeting nearly 3,000 students per grade, the sample ensures that estimates at the 

grade level achieve the required precision levels. 

2.2.3.3 Sex Group Estimates

The large sample size permitted analysis by sex without any special considerations in the sampling 

plan. During the class selection process, frames of eligible classes from co-educational schools in 

which classrooms were segregated by sex (i.e., an all-male or all-female class) were avoided, if 

possible.

2.2.3.4 Race/Ethnicity Group Estimates

In order to support separate analysis of the data for non-Hispanic white, non-Hispanic black and 

Hispanic students, in total and by school level, adequate sample sizes were required by the design 

for subgroups defined by: 1) school level by racial grouping; or 2) by sex grouping. Sample sizes 

were not designed, however, to support detailed analyses by sex and school level within 

racial/ethnic subgroups (e.g., middle school Hispanic males).

2.3 Sampling Methods

This section describes the methods used in the selection of PSUs, schools, grades, and classes of 

students. In this process, we define the probabilities of selection associated with the various 

sampling stages as follows:

 Probability of selecting PSUs

 Probability of selecting schools

 Probability of selection of grades

 Probability of selecting classes and students

These probabilities provide the basis for the sampling weights discussed in Chapter 4.

The overall probability of selection for a student is the product of the probability of selection of 

the PSU, which contains a group of schools, multiplied by the conditional probability of selecting 
Methodology Report: 2014 National Youth Tobacco Survey

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the student's school and the conditional probability of selecting the student's class. These steps are 

detailed in the selection below.

2.3.1 Primary Sampling Unit

Selection

Within each first-stage stratum, the PSUs were sorted by five-digit ZIP Code to attain a form of 

implicit geographic stratification. Implicit stratification, coupled with the PPS sampling method 

described below, ensures geographic sample representation. With PPS sampling, the selection 

probability for each PSU is proportional to the PSU’s measure of size.

The following systematic sampling procedures were applied to the stratified frame to select a PPS 

sample of PSUs.

 Select 93 PSUs with a systematic random sampling method within each stratum. The 

method applies within each stratum a sampling interval computed as the sum of the 

measures of size for the PSUs in the stratum divided by the number of PSUs to be 

selected in the stratum.

 Subsample at random 77 of the sample PSUs for the large high school sample. (Recall 

that there is no subsampling of large middle schools.)

 Subsample at random 12 of the sample PSUs for the medium school sample for the 

middle school sample and 8 of the sample PSUs for the medium high school sample.

 Subsample at random 13 of the sample PSUs for the small high school sample and 17 

PSUs for the small middle school sample. 

Probability

If MOSklm is the measure of size for school k in PSU l in stratum m and if Km is the number of 

PSUs to be selected in stratum m, then Pp

lm is the probability of selection of PSU l in stratum m:

















MOS

MOS

P = K

.m

lm

m

P

lm
Methodology Report: 2014 National Youth Tobacco Survey

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2.3.2 Schools

Selection

For large schools, one high school and one middle school were selected with PPS systematic 

sampling within a PSU. The schools were selected into the sample with probability proportional 

to the measure of size. (MOS). 

Small and medium schools were sampled independently from large schools; they were set in two 

separate strata sampled at lower rates. This approach was implemented by drawing subsample

PSUs for small and medium school sampling as described earlier. One small school or medium 

school was then selected in each subsampled PSU with probability proportional to the MOS.

Replacement of Schools/School Systems

We did not replace refusing school districts, schools, classes, or students. We allowed for school 

and student nonresponse by inflating the sample sizes to account for nonresponse. With this 

approach, all schools can be contacted in a coordinated recruitment effort, which is not possible 

for methods that allow for replacing schools.

Probability

The probability of selecting large school k in PSU l and stratum m, PLS

klm, at each level was 

computed as follows:

















MOS

MOS

P =

.lm

LS klm

klm

For large high schools, the selection probability incorporates an additional factor, 77/93, associated 

with the subsampling of PSUs for these schools.

For medium schools, one school was drawn from each subsampled PSU at each level, so the 

probability of selection of a medium school then becomes,

 

















MOS

MOS

P =

.lm

MS klm

klm 12/ 93

for medium middle schools and

 

















MOS

MOS

P =

.lm

HS klm

klm 8/ 93

for medium high schools.
Methodology Report: 2014 National Youth Tobacco Survey

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For small schools, one school was drawn from subsampled PSU at each level, so the probability 

of selection of a small school for each level then becomes

 

















MOS

MOS

P =

.lm

MS klm

klm 17 / 93

for small middle schools, and 

 

















MOS

MOS

P =

.lm

HS klm

klm 13/ 93

for small high schools.

2.3.3 Grades

Selection

Except for linked schools, all eligible grades were included in the class selection for each school.

In linked schools, grades were selected independently. One component school was selected to 

provide classes at each grade level, and grades within component schools were drawn with 

probability proportional to grade enrollment.

Probability

Most SSUs in the sample contained one component school. In these cases, all eligible grades were 

selected so that the probability of selecting a grade was 1.0.

In SSUs that were made up of component schools, the selection of each component school at each 

grade is made with PPS sampling. The school selections from each component school at each 

grade level were made independently.

We denote this PG

jklm the probability of selecting grade j in SSU k, in PSU l, stratum m. For the j

th

grade within SSU k, this probability is equal to the ratio of the number of students at grade j in the 

component school to the total enrollment in grade j across all component schools within the SSU.

2.3.4 Classes

Selection

In large schools, an average of 1.46 classes per grade were selected by selecting 2 classes per grade 

in 46% of the selected large schools and one class per grade in the remaining large schools. The 

double class sampling took place in schools with greater than 3% non-Hispanic black enrollment 

and one class per grade in the remaining schools.

One class per grade was selected in medium schools.

In small schools, that is, those that could not support a full class selection at each grade, all students 

in all eligible grades were taken into the sample.
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All students in a selected class who could complete the survey without special assistance were 

considered eligible and offered the opportunity to participate in the survey. Refusing students were 

not replaced. Nonresponse at the student level was accounted for in the sample size using an 

average per class yield that assumed student response rates derived from historical experience with 

the NYTS.

A set of classes was identified for each school at each grade level such that every student in a given 

grade level was enrolled in exactly one of the classes in the set. For example, a required English 

course might be used. If the school’s estimated non-Hispanic black enrollment exceeded 3%, two 

classes were randomly selected, without replacement, from the list. Otherwise, one class was 

randomly selected. Selections were made at all eligible grade levels in the school.

Probability

The probability of selection of a class when there are Cjklm classes at grade j in school k, PSUi, 

stratum m is just 1/Cjklm or 2/Cjklm depending on whether one or two classes are taken in the school. 

All students in a selected class were chosen, so the probability of selection of a student is the same 

as the class (i.e., 1/Cjklm or 2/Cjklm). 

Note that the probability of student selection within a class does not vary by race, ethnicity, or sex. 

We denote this probability as PC

ijklm as the probability of selecting class i in grade j, school k, PSU 

l, stratum m. Since every student in a selected class is also selected, the probability of selecting 

any student in class i, grade j, school k, PSU l, stratum k, is also equal to PC

ijklm.
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CHAPTER 3—NYTS DATA COLLECTION

3.1 Survey Instrument

The NYTS collects data on key short-term, intermediate, and long-term tobacco prevention and 

control outcome indicators. The 2014 survey instrument included a total of 81 questions, with the 

first 5 collecting student demographic information and the remaining measuring a comprehensive 

set of tobacco-related topics (Appendix A). Specific areas covered by the survey included: 

prevalence of tobacco product use; knowledge of and attitudes toward tobacco use; pro- and 

antitobacco media and advertising; minors’ access to tobacco products; nicotine dependence; 

cessation attempts; exposure to second-hand smoke; harm perceptions; exposure to tobacco 

product warnings; and tobacco use prevention school curricula.

3.2 Recruitment Procedures

The schools selected to participate in the 2014 NYTS were located in 36 different States. 

Recruitment began in May 2013 with calls to State Departments of Education and Health. Letters 

of support were obtained from various State agencies and used in mailings to districts and schools. 

A date for survey implementation was selected to optimize the efficiency of data collection while 

accommodating school schedules. In selecting a date, convenience to the school and its calendar 

were considered. Additionally, an effort was made to schedule groups of schools from the same 

school district or PSU around the same time to facilitate efficient travel to and survey 

implementation within selected schools. Recruiters used an electronic calendar on a secure shared 

drive to facilitate communication and to avoid scheduling two schools for the same data collector 

on the same day.

3.3 Survey Administration

Survey administration in the schools began on February 10, 2014, immediately after data collector 

training, and continued until June 13, 2014. Each data collector visited an average of three schools 

per week. While the details of each data collection varied, there were six core steps followed for 

every school: 1) precontact call with the principal or lead contact prior to arrival at the school; 2) 

entry meeting with the principal or lead contact; 3) entry meeting with teacher or group of teachers 

prior to survey administration; 4) survey administration; 5) postsurvey meeting with the teacher or 

teachers; and 6) postsurvey meeting with the principal or lead contact prior to leaving the school. 

Most survey administrations could be completed in 1 day, while at other times, due to the number 

of classes selected or alternating block schedules, the data collector needed to return for a second 

day. Procedures were designed to protect students’ privacy by assuring that student participation 

was anonymous and voluntary. Students completed a self-administered scannable questionnaire 

booklet via pencil and paper.

3.3.1 Data Collection Staffing

Data collectors were recruited from a pool of previously trained data collectors, as well as retired 

teachers associations, school health networks, and a variety of health education organizations. Data 

collector training was conducted on February 5–6, 2014. Key components of the training included 

the following:
Methodology Report: 2014 National Youth Tobacco Survey

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 Precontact activities with the schools

 Entry and exit meetings with school officials

 Data collection protocols

 Follow-up activities

 Communication with headquarters staff

3.3.2 Field Procedures

After schools had been recruited, classes selected, and a date scheduled, each school received a 

packet of presurvey materials. These materials included all the information necessary to prepare 

the school for data collection. Teacher packets contained the parental permission forms that had to 

be given out to all students in the selected classes prior to data collection. The timing of these 

presurvey packet mailings was determined in part by the type of permission form being used by 

the school. Passive parental permission forms, or forms returned only if the parents do not want 

their child to participate, were sent approximately 1 week prior to the scheduled date of data 

collection in the majority of schools. Active parental permission forms, forms that must be returned 

with the parent’s signature in order for the child to participate, were sent out at least 2 weeks prior 

to the scheduled date of data collection for schools that require active consent. Follow-up calls 

were made to the selected schools to answer any questions and to make sure materials were 

received and distributed to selected classes and students.

On a weekly basis, data collectors received mailings containing their assignments for the coming 

week, travel and logistics information, and their must-read weekly bulletin. Weekly bulletins 

underlined key performance issues, corrected misconceptions, provided consistent direction on 

any procedural changes, and kept everyone abreast of the latest must-have information. In addition 

to these mailings, boxes of survey supplies were sent to data collectors, either to the data collector’s 

home or hotel. These boxes contained all supplies necessary for completing the data collection, 

including questionnaires, data envelopes, field forms, and pencils. Data collectors were supplied 

with extra materials for emergency packs as well, which they carried with them at all times.

3.3.3 Classroom Selection

Students were selected for participation by default via the selection of whole classes (i.e., all 

students enrolled in a selected class were eligible to take the survey). The frames from which 

classes were chosen were constructed such that eligible students had one and only one chance of 

being selected. However, at times the specific method of selecting classes varied from school to 

school, according to how a school’s class schedule was structured. Typically, classes were selected 

from a list of required core courses such as English, social studies, math, or science. Among middle 

school students, and among high school students in a few States, physical education and/or health 

also were considered core courses. However, in a small number of schools, it was difficult to 

develop an appropriate frame using this approach. Therefore, in these schools, classes were 

selected by using a time of day (i.e., second period) when all eligible students were scheduled to 

be attending a class of one kind or another as the frame, and randomly selecting from all classes 

held at this time. Lastly, in some schools, school homerooms were used as the frame for class 

selection. 
Methodology Report: 2014 National Youth Tobacco Survey

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3.4 Participation Rates

Across the nine previous cycles of the NYTS, the school participation has averaged 86%, with a 

low of 75%. Student participation has averaged 91% with a low of 88%, and the overall response 

rate has averaged 78%. To be conservative, we assumed slightly lower values in developing the 

sample design for the 2014 NYTS: an assumed overall participation rate of 77%.

The actual response rates in 2014 differed from our projections: an actual school participation rate 

of 80.2% and a student participation rate of 91.4%. The overall participation rate, the product of 

the school-level and student-level participation rates was 73.3%. While the participation rate is 

slightly lower than the levels assumed in the projections, the shortfall has no meaningful impact 

on the estimation precision. As seen below, however, some design modifications may be 

recommended to increase the yields achieved for black students.

The 2014 NYTS data file contains responses from 22,007 students compared to the 21,078 

responding students anticipated by the design. Exhibit 3-1 shows that student yields were lower 

than targeted for non-Hispanic Blacks, with a shortfall of 76 and 255 students for high and middle 

schools, respectively. Among Hispanics, yields far exceeded the targets at both levels. 

EXHIBIT 3-1: SAMPLE YIELDS FOR NON-HISPANIC BLACK AND HISPANIC STUDENTS BY SCHOOL LEVEL

Subgroup Projected Participants Actual Participants

Middle School non-Hispanic Blacks 1,775 1,520

Middle School Hispanics 1,775 3,006

High School non-Hispanic Blacks 1,975 1,899

High School Hispanics 1,975 2,933
Methodology Report: 2014 National Youth Tobacco Survey

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CHAPTER 4—WEIGHTING OF NYTS RESPONSE DATA

4.1 Overview

This section describes the procedures used to weight the data collected in the NYTS 2014. The 

process involved the steps outlined below:

 Sampling weights

 Nonresponse adjustments

 Weight trimming

 Poststratification to national estimates of racial totals by grade, sex and school type

This section focuses on the development of the weights for the student response data. The final 

student level response data were weighted to reflect the initial probabilities of selection and 

nonresponse patterns, to mitigate large variations in sampling weights, and to poststratify the data 

to known sampling frame characteristics.

4.2 Sampling Weights

The base weight is the inverse of the probability of selection for each responding student. The base

weight is adjusted to compensate for nonresponse, to alleviate excess weight variation, and to 

match the weighted data to known control totals. The base weight is computed by inverting the 

probabilities of selection at each stage to derive a stage weight. For each respondent, the stage 

weights are multiplied to form the overall sampling weight assigned to each student.

The NYTS computation of sampling weights begins at the student sampling stage, and then moves 

to the school and PSU sampling stages. This sequence allows the student sampling weights to 

incorporate adjustments for student nonresponse. These adjustments, described next, use 

enrollment data by sex and by grade collected for each participating school. Because the process 

begins with the student weights within a given grade, school and PSU, we refer to these weights 

as conditional weights. 

4.2.1 Adjusted Conditional Student Weights

The adjusted conditional student weight is the student weight given the selection of the PSU, 

school, and grade. This weight is the product of the inverse of the probability of selection and a 

nonresponse adjustment within weighting classes based on grade and sex. Note that this step also 

includes an approach designed to limit the nonresponse adjustment factor, an early step to avoid 

extreme weights and hence to control the variability in the weights.

This three-step process is simplified algebraically (see Appendix B) and computed directly as the 

ratio of the number of enrolled students to the number of responding students in a given weighting

class within a school. The weighting class definition is set dynamically so as to avoid extreme 

weights, as described next.

We denote the student selection weight WR

cklm, where the subscripts k, l, and m refer to the school, 

PSU and stratum as before. The subscript c refers to the weighting class, described below. This 
Methodology Report: 2014 National Youth Tobacco Survey

Page 24 of 38

weight is computed as below, where N is the number of enrolled students for each school (the 

counts are provided by the school during data collection by grade and sex) and R is the number of 

responding students in weighting class c within a given school:

R

N

W =

cklm

R cklm

cklm

The weighting class c is defined by a sequence of rules that depends on the number of responding 

students. This is done to avoid large weights for classes with low numbers of respondents. This 

process operates entirely within schools.

Initially, the weighting class is defined by grade and sex within each school. We then combine 

weighting classes if the weight for the class exceeds a maximum value, C. This cap C is computed 

using the following equation:

min( 10, )

2

N

N

C =

cklm

cklm

cklm

The combination sequence first groups males and females within grade. Both the cap and the 

weight are then recomputed. If the weight still exceeds the cap, grades are combined. The process 

is repeated, and if the student weight still exceeds the cap, the school is taken as the weighting

class.

This has the effect, within school, of setting an upper limit on the weight of 2 in weighting classes 

with an enrollment of less than 10, and 20% of the enrollment in weighting classes with an 

enrollment of more than 10. Note that the cap could be exceeded, however, in the rare cases where 

the weighting class is collapsed to the school level.

4.2.2 School Sampling Weights

For large schools, the partial school weight is the inverse of the probability of selection of the 

school given that the PSU was selected:

P

1

=

MOS

MOS

W =

LS

klm klm

LS .lm

klm 















For small schools, the partial school weight is:

P

1

=

MOS

MOS

W =

SS

klm klm

SS .lm

klm 















(93/15)
Methodology Report: 2014 National Youth Tobacco Survey

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For medium schools, the partial school weight is:

P

1

=

MOS

MOS

W =

MS

klm klm

MS .lm

klm 















(93/12)

P

1

=

MOS

MOS

W =

HS

klm klm

HS .lm

klm 















(93/8)

4.2.3 Grade Sampling Weights

Grade selection occurs within linked schools where the grade is available in each of the linked 

schools, or school “components” that constitute the SSU. The partial weight for a grade, given the 

selection of the linked school containing it, is simply the inverse of the probability of selection 

described in Section 2.4. In a non-linked school, the weight is 1.0. We denote the grade weight as 

WG

jklm. 
Methodology Report: 2014 National Youth Tobacco Survey

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4.2.4 PSU Sampling Weights

The weight of the PSU is the inverse of the probability of selection of that PSU:

P

1

=

MOS

MOS

K

1

W =

P

lm lm

.m

m

P

lm 











For small and medium school selections, the supporting sample PSUs were drawn as a subsample.

(Subsampling of PSUs also was conducted for the large high schools.) This PSU subsampling 

component of the PSU weight is accounted for in the school selection probability and 

corresponding weight.

4.2.5 Overall Sampling Weight

The overall sampling weight is formed as the product of the stage selection weights. This weight, 

WT1, is then adjusted for nonresponse, trimmed, and poststratified to control totals, as described in 

the following sections. This weight is computed as:











W =W W W W

W =W W W W

W =W W W W

R

hijklm

G

jklm

SS

klm

P

lm

T1

hijklm

R

hijklm

G

jklm

MS

klm

P

lm

T1

hijklm

R

hijklm

G

jklm

LS

klm

P

lm

T1

hijklm

for large, medium and small schools, respectively, where the weights in the latter portions of the 

equations are defined in the preceding sections.

4.3 Nonresponse Adjustments

This section describes how weights are adjusted for nonparticipation by entire schools, using strata 

as weighting classes.

The adjustment process is different in small schools than in medium and large schools, as 

represented by the following equations for the adjustment factor.































S S

klm

S S

klm

P

l m

k,l

S S

klm

S S

klm

P

l m

S S k,l

M S LS

klm

M S LS

klm

P

l m

k,l responding

M S LS

klm

M S LS

klm

P

l m

M S LS k,l

m

W W MOS

W W MOS

A =

W W MOS

W W MOS

A =

smallschools with respondents

smallschoolssampled

, ,

mediumand large,schools

, ,

, mediumand large,schoolssampled









The first equation applies to medium and large schools combined, and the second applies to small 

schools. Note that this adjustment is made within stratum for medium and large schools and across 

the whole sample for small schools. The student weight, adjusted for nonresponse, is ASS

lm WT1hijklm 

for small schools and AMS,LS

lm WT1hijklm for medium and large schools.
Methodology Report: 2014 National Youth Tobacco Survey

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To avoid very large weight adjustment factors, which may lead to variance increases, weighting 

classes combined the top two sampling strata in terms of racial/ethnic minority concentrations. 

These weighting cells were created for computing nonresponse adjustments only—the collapsed 

strata not kept on the analytic file. Specifically, weighting cells combined the following pairs of 

strata: BU4 and BU3; BR3 and BR4; HU3 and HU4; and HR3 and HR4. School response rates by 

weighting class, and the resulting nonresponse adjustment factors, are detailed in Exhibit 4-1. Note 

that the weighting classes are defined using collapsed sampling strata.

EXHIBIT 4-1: MEDIUM AND LARGE SCHOOL NONRESPONSE

School 

Level

Stratum 

(Nonresponse)

Sampled 

Schools

Responding 

Schools

Percent 

Responding

Nonresponse 

Adjustment

HS BR1 13 10 76.9% 1.3

HS BR2 5 5 100.0% 1.0

HS BR3 and BR4 6 6 100.0% 1.0

HS BU1 10 8 80.0% 1.2

HS BU2 4 3 75.0% 1.2

HS BU3 and BU4 6 3 50.0% 2.0

HS HR1 10 9 90.0% 1.2

HS HR2 4 3 75.0% 1.4

HS HR3 and HR4 5 4 80.0% 1.2

HS HU1 13 9 69.2% 1.4

HS HU2 4 4 100.0% 1.0

HS HU3 and HU4 12 11 91.7% 1.1

HS Total 92 75 81.5%

MS BR1 16 12 75.0% 1.3

MS BR2 6 6 100.0% 1.0

MS BR3 and BR4 9 6 66.7% 1.6

MS BU1 16 11 68.8% 1.3

MS BU2 3 2 66.7% 1.4

MS BU3 and BU4 6 6 100.0% 1.0

MS HR1 21 18 85.7% 1.1

MS HR2 5 3 60.0% 1.5

MS HR3 and HR4 6 6 100.0% 1.0

MS HU1 19 13 68.4% 1.4

MS HU2 13 10 76.9% 1.3

MS HU3 and HU4 16 15 93.8% 1.1

MS Total 136 108 79.4%

Gross Total 228 183 80.0%
Methodology Report: 2014 National Youth Tobacco Survey

Page 28 of 38

4.4 Weight Trimming

Extreme variation in sampling weights can cause inflated sampling variances, and offset the 

precision gained from a well-designed sampling plan. One strategy to compensate for this is to 

trim extreme weights and distribute the trimmed weight among the untrimmed weights. The 

method we used6is based on a similar procedure employed for the National Assessment of 

Educational Progress (NAEP).

The trimming is an iterative procedure. During each iteration, an optimal weight (Wo)

7

, is 

calculated from the sum of the squared weights in the sample. Each weight Wi is then marked and 

trimmed if it exceeds that optimal weight. The trimmed weight is summed within grade and spread 

out proportionally over the unmarked cases in the grade. This process is repeated for 20 iterations 

or until no weight is being trimmed.

Wok is determined by the following:



















n

w

W = c

2

k

n

k=1

2

1

ok

The constant, “c,” is arbitrary. Setting it to a low level will generate high levels of trimming, while 

increasing it will reduce the level of trimming. For the current study, “c” has been set so that 

approximately 5% of the weight is trimmed in the first iteration of the trimming algorithm.

Let Wik and Wok be the weight for the ith case and the optimum weight for the kth iteration, 

respectively, and define tik as 1 if Wik is greater than or equal to Wok, and 0 otherwise.

Then the trimmed weight for the k + 1 iteration is defined as follows:





























 







if W <W

W (1 -t )

W

t W

W 1-

W if W W

W =

i k o k

i k i k

n

i=1

i k

i k o k

i k

n

i=1

o k i k o k

i ,k+1

Trimming has the effect of reducing the variation of the weights substantially in each trimming 

class and overall.

 

6

Potter, F. (1988). Survey of Procedures to Control Extreme Sampling Weights. American Statistical Association 

1988 Proceedings: Survey Research Methods Section, pp. 225–230.

7

In the following discussion, the subscripts are used to indicate the iterative process used in the trimming algorithm.

To avoid overly cumbersome notation, we have omitted the subscripts indexing the sampling stages. W, the initial 

weight, is taken as the nonresponse adjusted sampling weight described in the preceding section. The subscripts k

and n represent the number of iterations and the number of cases/weights, respectively.
Methodology Report: 2014 National Youth Tobacco Survey

Page 29 of 38

4.5 Poststratification to National Student Population Estimates

To obtain accurate counts of students in schools considered eligible for the NYTS by sexgrade, 

and race/ethnicity for use in poststratification, we turned to two school universe surveys conducted 

by NCES. Raw school-level data files were downloaded and processed to mirror eligibility 

requirements imposed on the sampling frame.

National estimates of racial/ethnic percentages were obtained from two sources: 1) private school 

enrollments by grade and five racial/ethnic groups were obtained from the Private School Universe 

Survey (PSS); and 2) public school enrollments by grade, sex, and five racial/ethnic categories 

were obtained from CCD, both produced by NCES (Appendix C). These databases were combined 

to produce the enrollments for all schools, and to develop population percentages to use as controls 

in the poststratification step.

Specifically, population control totals for public school enrollments were taken from the most 

recent NCES CCD Public Elementary/Secondary School Universe Survey (2010–11).8 Records 

for special education, vocational, and other/alternative schools were deleted prior to computing 

control totals. Control totals for private school enrollments were taken from the NCES PSS, School 

Year 2009−10 (most recent PSS data); this file also was restricted to “regular” schools.

Given a national estimate of student counts Ra and a weighted response total of Pa for 

poststratification adjustment class “a,” the poststratification factor was the ratio of Ra to Pa. Exhibit 

4-2 gives the population control totals used in poststratification adjustments alongside the sum of 

the weights in each poststratum cell, as well as the adjustment factors calculated as the ratio of 

these two totals. More specifically, the adjustments in column G in this exhibit are computed as 

E/F, control total for the cell divided by the weight sum in the cell.

Poststratification adjustment cells were defined by school type, grade, sex and race/ethnicity. 

Because estimates are typically reported separately for middle schools and high schools, the weights 

were adjusted separately for both subpopulations. Within the private school adjustment cells, sex 

was omitted, as enrollments by sex were not available for these schools. This is indicated by a 

“Combined” sex in Exhibit 4-2. Also within private schools, the racial/ethnic groups were collapsed 

to preclude small numbers of students in the adjustment classes. For the public schools, five 

racial/ethnic categories were used: non-Hispanic white; non-Hispanic black; Hispanic; non-Hispanic 

Asian/ Pacific Islander; and non-Hispanic Native American/Alaska Native (Appendix C).

 

8 Common Core of Data, National Center for Education Statistics http://nces.ed.gov/ccd/. School Year 2010–11.
Methodology Report: 2014 National Youth Tobacco Survey

Page 30 of 38

EXHIBIT 4-2: POSTSTRATIFICATION ADJUSTMENTS

School 

Type Grade Race/Hispanic Origin Sex

(E) 

Control 

Total

(F) 

Weighted 

Estimate

No. of 

Cases

(G) 

Poststratification 

Adjustment

Private 6 Combined Combined 306,460 347,636 178 0.88156

Private 7 Combined Combined 305,170 222,678 167 1.37046

Private 8 Combined Combined 305,489 326,797 178 0.93480

Private 9 Combined Combined 281,606 205,659 107 1.36929

Private 10 Combined Combined 279,592 221,519 117 1.26216

Private 11 Combined Combined 275,027 187,267 102 1.46864

Private 12 Combined Combined 271,152 162,703 106 1.66654

Public 6

Non-Hispanic Asian and 

Pacific Islander Female 83,993 103,811 103 0.80910

Public 6 Non-Hispanic Black Female 293,043 239,227 276 1.22496

Public 6 Hispanic Female 437,910 490,908 494 0.89204

Public 6

Non-Hispanic Native 

American Female 22,815 91,203 71 0.25015

Public 6 Non-Hispanic White Female 961,220 749,440 656 1.28258

Public 6

Non-Hispanic Asian and 

Pacific Islander Male 86,306 87,415 98 0.98732

Public 6 Non-Hispanic Black Male 305,483 269,934 300 1.13170

Public 6 Hispanic Male 456,836 572,043 561 0.79860

Public 6

Non-Hispanic Native 

American Male 23,708 113,762 95 0.20840

Public 6 Non-Hispanic White Male 1,021,460 748,834 652 1.36407

Public 7

Non-Hispanic Asian and 

Pacific Islander Female 82,961 94,515 67 0.87775

Public 7 Non-Hispanic Black Female 292,644 260,596 255 1.12298

Public 7 Hispanic Female 430,449 584,601 528 0.73631

Public 7

Non-Hispanic Native 

American Female 22,838 98,331 66 0.23226

Public 7 Non-Hispanic White Female 968,116 865,517 704 1.11854

Public 7

Non-Hispanic Asian and 

Pacific Islander Male 86,022 83,863 85 1.02575

Public 7 Non-Hispanic Black Male 303,320 291,794 280 1.03950

Public 7 Hispanic Male 449,797 657,112 555 0.68451

Public 7

Non-Hispanic Native 

American Male 23,776 80,989 69 0.29357

Public 7 Non-Hispanic White Male 1,024,015 937,254 741 1.09257
Methodology Report: 2014 National Youth Tobacco Survey

Page 31 of 38

School 

Type Grade Race/Hispanic Origin Sex

(E) 

Control 

Total

(F) 

Weighted 

Estimate

No. of 

Cases

(G) 

Poststratification 

Adjustment

Public 8

Non-Hispanic Asian and 

Pacific Islander Female 85,580 95,227 83 0.89870

Public 8 Non-Hispanic Black Female 288,628 295,210 277 0.97770

Public 8 Hispanic Female 422,768 639,572 554 0.66102

Public 8

Non-Hispanic Native 

American Female 22,312 49,971 47 0.44651

Public 8 Non-Hispanic White Female 968,394 869,283 686 1.11402

Public 8

Non-Hispanic Asian and 

Pacific Islander Male 89,334 90,511 79 0.98700

Public 8 Non-Hispanic Black Male 295,815 303,686 286 0.97408
Methodology Report: 2014 National Youth Tobacco Survey

Page 32 of 38

EXHIBIT 4-2: POSTSTRATIFICATION ADJUSTMENTS (CONTINUED)

School 

Type Grade Race/Hispanic Origin Sex

(E) 

Control 

Total

(F) 

Weighted 

Estimate

No. of 

Cases

(G) 

Poststratification 

Adjustment

Public 8 Hispanic Male 437,034 597,939 506 0.73090

Public 8

Non-Hispanic Native 

American Male 22,800 86,784 67 0.26272

Public 8 Non-Hispanic White Male 1,022,119 906,212 718 1.12790

Public 9

Non-Hispanic Asian and 

Pacific Islander Female 87,415 151,401 91 0.57738

Public 9 Non-Hispanic Black Female 321,224 378,173 237 0.84941

Public 9 Hispanic Female 441,642 636,775 388 0.69356

Public 9

Non-Hispanic Native 

American Female 23,819 71,285 43 0.33413

Public 9 Non-Hispanic White Female 1,015,797 954,198 596 1.06455

Public 9

Non-Hispanic Asian and 

Pacific Islander Male 91,952 142,060 90 0.64728

Public 9 Non-Hispanic Black Male 344,666 399,004 228 0.86382

Public 9 Hispanic Male 472,389 727,924 414 0.64895

Public 9

Non-Hispanic Native 

American Male 25,536 67,946 36 0.37583

Public 9 Non-Hispanic White Male 1,082,621 1,079,589 691 1.00281

Public 10 Asian and Pacific Islander Female 87,245 137,173 98 0.63602

Public 10 Non-Hispanic Black Female 298,317 437,994 266 0.68110

Public 10 Hispanic Female 399,950 617,521 421 0.64767

Public 10 Non-Hispanic Native 

American Female 22,167 67,441 32 0.32869

Public 10 Non-Hispanic White Female 996,754 907,303 602 1.09859

Public 10 Non-Hispanic Asian and 

Pacific Islander Male 91,740 144,639 96 0.63427

Public 10 Non-Hispanic Black Male 302,961 327,576 230 0.92486

Public 10 Hispanic Male 414,302 583,150 408 0.71045

Public 10 Non-Hispanic Native 

American Male 23,140 41,956 28 0.55152

Public 10 Non-Hispanic White Male 1,042,852 1,103,116 701 0.94537

Public 11 Non-Hispanic Asian and 

Pacific Islander Female 83,060 144,618 100 0.57434

Public 11 Non-Hispanic Black Female 270,278 296,051 248 0.91294

Public 11 Hispanic Female 351,600 517,164 387 0.67986
Methodology Report: 2014 National Youth Tobacco Survey

Page 33 of 38

School 

Type Grade Race/Hispanic Origin Sex

(E) 

Control 

Total

(F) 

Weighted 

Estimate

No. of 

Cases

(G) 

Poststratification 

Adjustment

Public 11 Non-Hispanic Native 

American Female 20,462 25,316 18 0.80826

Public 11 Non-Hispanic White Female 955,058 845,960 579 1.12896

Public 11 Non-Hispanic Asian and 

Pacific Islander Male 87,816 125,553 106 0.69943

Public 11 Non-Hispanic Black Male 260,589 315,934 249 0.82482

Public 11 Hispanic Male 354,460 475,928 371 0.74477

Public 11 Non-Hispanic Native 

American Male 20,769 20,236 17 1.02633

Public 11 Non-Hispanic White Male 988,539 923,478 672 1.07045

Public 12 Non-Hispanic Asian and 

Pacific Islander Female 80,949 137,666 92 0.58801
Methodology Report: 2014 National Youth Tobacco Survey

Page 34 of 38

EXHIBIT 4-2: POSTSTRATIFICATION ADJUSTMENTS (CONTINUED)

School 

Type Grade Race/Hispanic Origin Sex

(E) 

Control 

Total

(F) 

Weighted 

Estimate

No. of 

Cases

(G) 

Poststratification 

Adjustment

Public 12 Non-Hispanic Black Female 259,801 296,168 245 0.87721

Public 12 Hispanic Female 324,717 503,785 361 0.64455

Public 12 Non-Hispanic Native 

American Female 19,339 35,662 23 0.54227

Public 12 Non-Hispanic White Female 941,752 793,320 554 1.18710

Public 12 Non-Hispanic Asian and 

Pacific Islander Male 84,706 141,448 110 0.59885

Public 12 Non-Hispanic Black Male 240,128 275,861 239 0.87047

Public 12 Hispanic Male 318,489 462,472 363 0.68867

Public 12 Non-Hispanic Native 

American Male 19,505 34,231 22 0.56980

Public 12 Non-Hispanic White Male 969,959 895,150 641 1.08357

Following poststratification, the adjusted weights sum to the population control totals.

4.6 Analysis Strata and Variance Estimation

Sampling variances for complex sampling designs can be estimated using one of several methods, 

including linearized estimators and balanced repeated replication. These methods are implemented 

with a variety of software packages, including SUDAAN, WesVar, Stata and SAS using special 

sample survey procedures (such as Proc SurveyMeans in SAS Version 9). The 2014 NYTS data 

were prepared for estimating variances using the method of linearized estimators.

Because estimates are typically reported separately for middle schools and high schools, analysis 

strata need to ensure that each stratum has two or more PSUs for variance estimation within each 

subpopulation (middle schools and high schools separately). 

As noted earlier, the allocation ensured that every stratum had at least two PSUs in the sample. 

This does not necessarily translate to two PSUs with valid student data for each school level 

(middle schools and high schools) in every stratum due to the effects of nonresponse at the school 

level. In particular, nonparticipating schools may lead to PSUs without student data for a given 

school level.. 

Exhibit 4-3 displays the correspondence between the sampling strata and the analysis strata, which 

are represented by two variables on the analysis file. All strata/level combinations but one had at 

least two PSUs. As a result, strata BU3 and BU4 were collapsed (into analysis stratum 113) 

because BU4 had only one PSU for one school level. Thus, the analytic file contains 15 values in 

the analysis strata variable and 16 values in the design strata variable.

In addition, stratum codes used in sampling and weighting were converted to a numeric “analysis 

stratum” code for use in SUDAAN, which requires numeric variables.
Methodology Report: 2014 National Youth Tobacco Survey

Page 35 of 38

EXHIBIT 4-3: SAMPLING AND ANALYSIS STRATUM CODING SCHEMES

High non-Hispanic Black High Hispanic

Sampling Stratum Code Analysis Stratum Code

Sampling Stratum 

Code

Analysis Stratum Code

BR1 101 HR1 201

BR2 102 HR2 202

BR3 103 HR3 203

BR4 103 HR4 203

BU1 111 HU1 211

BU2 112 HU2 212

BU3 and BU4 113 HU3 213

HU4 214

Exhibit 4-4 presents selected key survey estimates and their sampling errors estimated using Taylor 

series linearization methods, which are usually employed by NYTS data analysts, and implemented 

with SUDAAN or similar software (e.g., SAS Proc SurveyMeans). Specifically, the Exhibit presents 

the percent and standard error of the percent for estimates of current use of selected tobacco products 

separately for high schools (Exhibit 4-4a) and middle schools (Exhibit 4-4b).

EXHIBIT 4-4A: CURRENT USE ESTIMATES FOR SELECTED TOBACCO PRODUCTS FOR HIGH SCHOOL STUDENTS

(STANDARD ERRORS IN PARENTHESES)

Current Use

Product Overall Female Male Non-Hispanic 

White

Non-Hispanic 

Black Hispanic

Cigarettes 9.2% (0.6) 7.9% (0.6) 10.6% (0.9) 10.8% (0.8) 4.5% (0.6) 8.8% (0.9)

Cigar 8.2% (0.5) 5.5% (0.5) 10.8% (0.7) 8.3% (0.6) 8.8% (1.2) 8.0% (0.8)

Smokeless 

Tobacco 5.5% (0.5) 1.2% (0.2) 9.9% (1.0) 7.8% (0.8) 1.1% (0.3) 3.1% (0.5)

Hookah 9.4% (0.6) 9.8% (0.8) 8.9% (0.7) 9.4% (0.7) 5.6% (0.7) 13.0% (1.4)

Electronic 

Cigarettes 13.4% (1.2) 11.9% (1.2) 15.0% (1.4) 15.3% (1.6) 5.6% (1.2) 15.3% (1.9)
Methodology Report: 2014 National Youth Tobacco Survey

Page 36 of 38

EXHIBIT 4-4B: CURRENT USE ESTIMATES FOR SELECTED TOBACCO PRODUCTS FOR MIDDLE SCHOOL STUDENTS

(STANDARD ERRORS IN PARENTHESES)

Current Use

Product Overall Female Male Non-Hispanic 

White

Non-Hispanic 

Black Hispanic

Cigarettes 2.5% (0.2) 2.0% (0.3) 3.0% (0.4) 2.2% (0.3) 1.7% (0.4) 3.7% (0.6)

Cigar 1.9% (0.2) 1.4% (0.3) 2.4% (0.4) 1.4% (0.4) 2.0% (0.4) 2.9% (0.4)

Smokeless 

Tobacco 1.6% (0.2) 1.1% (0.3) 2.1% (0.4) 1.7% (0.4) .9% (0.3) 1.3% (.3)

Hookah 2.5% (0.3) 2.6% (0.4) 2.4% (0.3) 1.4% (0.2) 1.5% (0.5) 5.6% (0.7)

Electronic 

Cigarettes 3.9% (0.5) 3.3% (0.5) 4.5% (0.6) 3.1% (0.5) 3.8% (0.7) 6.2% (0.8)

Example specifications for applying the method with both SAS and SUDAAN are provided below 

for computing prevalence.

Example: Estimates, Current Use by School Type

SAS:

SAS:

Proc Surveymeans Data=nyts2014 mean;

Var ccigt_r ccigar_r cslt_r chookah_r celcigt_r;

Class ccigt_r ccigar_r cslt_r chookah_r celcigt_r;

Stratum stratum2;

Cluster psu2;

Weight wt;

Domain Schooltype Schooltype*Sex Schooltype*Race_S;

Title “NYTS 2014, Estimates by School Type, by School Type and Sex Cross-Classified, and by School Type and 

Race/Ethnicity Cross-Classified”;

run;

SUDAAN:

Proc Descript Data=nyts2014 Filetype= SAS Design=WR;

Var ccigt_r ccigar_r cslt_r chookah_r celcigt_r;

Catlevel 1 1 1 1 1;

Nest Stratum2 PSU2 / Missunit;

Weight wt;

Subgroup School Sex Race_S;

Levels 2 2 3;

Tables School School*Sex School*Race_S;

Title “NYTS 2014, Estimates by School Type, by School Type and Sex Cross-Classified, and by School Type and 

Race Cross-Classified”;

Print Percent Sepercent / Style=NCHS;

run;
Appendix A

Questionnaire
Methodology Report: 2014 National Youth Tobacco Survey

A-1

APPENDIX A. QUESTIONNAIRE

Form Approved

OMB No.: 0920-0621 

Expiration Date: 01/31/2015

National Youth

Tobacco Survey (NYTS)

2014 Questionnaire

Thank You Very Much For Your Help.

This survey is about tobacco. We would like to know about you and things you do that may affect 

your health. Your answers will be used for programs for young people like yourself.

DO NOT write your name on this survey. The answers you give will be kept private. 

NO one will know what you write. Answer the questions based on what you really do and know.

Completing the survey is voluntary. Whether or not you answer the questions will not affect your 

grade in this class. Try to answer all the questions. If you do not want to answer a question, just 

leave it blank. There are no wrong answers.

The questions that ask about your background will only be used to describe the types of 

students completing this survey. The information will not be used to find out your name. No 

names will ever be reported. 

Please read every question. Try to answer all the questions. Fill in the circles in the booklet 

completely. When you are finished, follow the instructions of the person giving you the survey.

Public reporting burden for this collection of information is estimated to average 45 minutes per 

response, including time for reviewing instructions, searching existing data sources, gathering and 

maintaining the data needed, and completing and reviewing the collection of information. An agency may 

not conduct or sponsor, and a person is not required to respond to a collection of information unless it 

displays a currently valid OMB control number. Send comments regarding this burden estimate or any 

other aspect of this collection of information, including suggestions for reducing this burden to: CDC

Reports Clearance Officer, 1600 Clifton Road, NE, MS D-74, Atlanta, GA 30333, ATTN: PRA (0920-

0621).
Methodology Report: 2014 National Youth Tobacco Survey

A-2

The first five questions ask for some background 

information about you.

1. How old are you? 

a. 9 years old 

b. 10 years old 

c. 11 years old 

d. 12 years old 

e. 13 years old 

f. 14 years old 

g. 15 years old 

h. 16 years old 

i. 17 years old 

j. 18 years old 

k. 19 years old or older 

2. What is your sex? 

a. Male

b. Female 

3. What grade are you in? 

a. 6th

b. 7th

c. 8th

d. 9th

e. 10th

f. 11th

g. 12th

h. Ungraded or other grade 

4. Are you Hispanic, Latino/a, or Spanish origin (One 

or more categories may be selected)?

a. No, not of Hispanic, Latino/a, or Spanish origin

b. Yes, Mexican, Mexican American, Chicano or 

Chicana

c. Yes, Puerto Rican

d. Yes, Cuban

e. Yes, Another Hispanic, Latino/a, or Spanish 

origin

5. What race or races do you consider yourself to be? 

(You can CHOOSE ONE ANSWER or MORE 

THAN ONE ANSWER)

a. American Indian or Alaska Native

b. Asian

c. Black or African American

d. Native Hawaiian or Other Pacific Islander

e. White

The next five sections of questions ask about your use 

of particular kinds of tobacco products.

The first 13 questions are about smoking cigarettes.

6. Have you ever been curious about smoking a 

cigarette? 

a. Definitely yes 

b. Probably yes

c. Probably not

d. Definitely not

7. Have you ever tried cigarette smoking, even one 

or two puffs? 

a. Yes 

b. No 

8. Do you think you will smoke a cigarette in the next 

year?

a. Definitely yes 

b. Probably yes 

c. Probably not 

d. Definitely not 

9. Do you think that you will try a cigarette soon? 

a. Definitely yes 

b. Probably yes 

c. Probably not 

d. Definitely not
Methodology Report: 2014 National Youth Tobacco Survey

A-3

10. If one of your best friends were to offer you a 

cigarette, would you smoke it?

a. Definitely yes 

b. Probably yes 

c. Probably not 

d. Definitely not

11. How old were you when you first tried cigarette 

smoking, even one or two puffs?

a. I have never smoked cigarettes, not even one 

or two puffs

b. 8 years old or younger 

c. 9 years old

d. 10 years old

e. 11 years old

f. 12 years old

g. 13 years old

h. 14 years old

i. 15 years old

j. 16 years old

k. 17 years old

l. 18 years old

m. 19 years old or older

12. About how many cigarettes have you smoked in 

your entire life?

a. I have never smoked cigarettes, not even one 

or two puffs

b. 1 or more puffs but never a whole cigarette

c. 1 cigarette

d. 2 to 5 cigarettes

e. 6 to 15 cigarettes (about 1/2 a pack total)

f. 16 to 25 cigarettes (about 1 pack total)

g. 26 to 99 cigarettes (more than 1 pack, but less 

than 5 packs)

h. 100 or more cigarettes (5 or more packs)

13. During the past 30 days, on how many days did 

you smoke cigarettes?

a. 0 days

b. 1 or 2 days 

c. 3 to 5 days 

d. 6 to 9 days 

e. 10 to 19 days 

f. 20 to 29 days 

g. All 30 days

14. During the past 30 days, on the days you 

smoked, about how many cigarettes did you 

smoke per day? 

a. I did not smoke cigarettes during the past 30 

days

b. Less than 1 cigarette per day

c. 1 cigarette per day

d. 2 to 5 cigarettes per day

e. 6 to 10 cigarettes per day

f. 11 to 20 cigarettes per day

g. More than 20 cigarettes per day

15. When was the last time you smoked a cigarette, 

even one or two puffs? (PLEASE CHOOSE THE 

FIRST ANSWER THAT FITS)

a. I have never smoked cigarettes, not even one 

or two puffs

b. Earlier today 

c. Not today but sometime during the past 7 days

d. Not during the past 7 days but sometime 

during the past 30 days

e. Not during the past 30 days but sometime 

during the past 6 months

f. Not during the past 6 months but sometime 

during the past year

g. 1 to 4 years ago

h. 5 or more years ago
Methodology Report: 2014 National Youth Tobacco Survey

A-4

16. During the past 30 days, what brand of cigarettes 

did you usually smoke? (CHOOSE ONLY ONE 

ANSWER)

a. I did not smoke cigarettes during the past 30 

days

b. I did not smoke a usual brand

c. American Spirit

d. Camel

e. GPC, Basic, or Doral

f. Kool

g. Lucky Strike

h. Marlboro

i. Newport

j. Parliament

k. Virginia Slims

l. Some other brand not listed here 

m. Not sure

17. Menthol cigarettes are cigarettes that taste like mint.

During the past 30 days, were the cigarettes that 

you usually smoked menthol?

a. I did not smoke cigarettes during the past 30 days

b. Yes

c. No

d. Not sure

18. How likely is it that you will try to purchase cigarettes 

within the next 30 days? 

a. I do not smoke cigarettes

b. Very likely

c. Somewhat likely

d. Somewhat unlikely

e. Very unlikely

The next seven questions are about the use of cigars, 

cigarillos or little cigars such as Black and Mild, Swisher 

Sweets, Dutch Masters, White Owl, or Phillies Blunts.

19. Have you ever been curious about smoking a cigar, 

cigarillo, or little cigar such as Black and Mild, 

Swisher Sweets, Dutch Masters, White Owl, or 

Phillies Blunts? 

a. Definitely yes 

b. Probably yes

c. Probably not

d. Definitely not

20. Have you ever tried smoking cigars, cigarillos, or 

little cigars, such as Black and Mild, Swisher 

Sweets, Dutch Masters, White Owl, or Phillies 

Blunts, even one or two puffs?

a. Yes 

b. No 

21. Do you think that you will try a cigar, cigarillo or 

little cigar soon? 

a. Definitely yes 

b. Probably yes 

c. Probably not 

d. Definitely not

22. If one of your best friends were to offer you a 

cigar, cigarillo or little cigar, would you smoke it?

a. Definitely yes 

b. Probably yes 

c. Probably not 

d. Definitely not

23. How old were you when you first tried smoking a 

cigar, cigarillo, or little cigar, even one or two 

puffs?

a. I have never smoked cigars, cigarillos, or little 

cigars, not even one or two puffs

b. 8 years old or younger 

c. 9 years old 

d. 10 years old

e. 11 years old

f. 12 years old

g. 13 years old

h. 14 years old

i. 15 years old

j. 16 years old

k. 17 years old

l. 18 years old

m. 19 years old or older
Methodology Report: 2014 National Youth Tobacco Survey

A-5

24. During the past 30 days, on how many days did you 

smoke cigars, cigarillos, or little cigars?

a. 0 days

b. 1 or 2 days 

c. 3 to 5 days 

d. 6 to 9 days 

e. 10 to 19 days 

f. 20 to 29 days 

g. All 30 days 

25. During the past 30 days, on the days that you 

smoked, about how many cigars, cigarillos, or little 

cigars did you smoke per day?

a. I did not smoke cigars, cigarillos, or little cigars 

during the past 30 days

b. Less than 1 cigar, cigarillo or little cigar per day

c. 1 per day

d. 2 to 5 per day

e. 6 to 10 per day

f. 11 to 20 per day

g. More than 20 per day

The next four questions are about the use of chewing 

tobacco, snuff or dip. Do not think about using snus 

when you answer these questions.

26. Have you ever been curious about using chewing 

tobacco, snuff, or dip, such as Redman, Levi 

Garrett, Beechnut, Skoal, Skoal Bandits, or 

Copenhagen? 

a. Definitely yes 

b. Probably yes

c. Probably not

d. Definitely not

27. Have you ever used chewing tobacco, snuff, or dip, 

such as Redman, Levi Garrett, Beechnut, Skoal, 

Skoal Bandits, or Copenhagen, even just a small 

amount? 

a. Yes 

b. No 

28. How old were you when you used chewing 

tobacco, snuff, or dip for the first time?

a. I have never used chewing tobacco, snuff, or 

dip

b. 8 years old or younger 

c. 9 years old 

d. 10 years old

e. 11 years old

f. 12 years old

g. 13 years old

h. 14 years old

i. 15 years old

j. 16 years old

k. 17 years old

l. 18 years old

m. 19 years old or older

29. During the past 30 days, on how many days did 

you use chewing tobacco, snuff, or dip? 

a. 0 days 

b. 1 or 2 days 

c. 3 to 5 days 

d. 6 to 9 days 

e. 10 to 19 days 

f. 20 to 29 days 

g. All 30 days 

The next six questions are about the use of electronic 

cigarettes or e-cigarettes such as blu, 21st Century 

Smoke or NJOY.

30. Have you ever been curious about using an 

electronic cigarette or e-cigarette such as blu, 21st

Century Smoke or NJOY? 

a. Definitely yes 

b. Probably yes

c. Probably not

d. Definitely not

31. Have you ever tried an electronic cigarette or ecigarette such as blu, 21st Century Smoke or 

NJOY?

a. Yes 

b. No 
Methodology Report: 2014 National Youth Tobacco Survey

A-6

32. Do you think that you will try an electronic 

cigarette or e-cigarette soon? 

a. Definitely yes 

b. Probably yes 

c. Probably not 

d. Definitely not

33. If one of your best friends were to offer you an 

electronic cigarette or e-cigarette, would you use 

it?

a. Definitely yes 

b. Probably yes 

c. Probably not 

d. Definitely not

34. How old were you when you first tried using an 

electronic cigarette or e-cigarette?

a. I have never used electronic cigarettes or ecigarettes

b. 8 years old or younger 

c. 9 years old 

d. 10 years old

e. 11 years old

f. 12 years old

g. 13 years old

h. 14 years old

i. 15 years old

j. 16 years old

k. 17 years old

l. 18 years old

m. 19 years old or older

35. During the past 30 days, on how many days did 

you use electronic cigarettes or e-cigarettes such 

as blu, 21st Century Smoke, or NJOY?

a. 0 days

b. 1 or 2 days

c. 3 to 5 days

d. 6 to 9 days

e. 10 to 19 days

f. 20 to 29 days

g. All 30 days

The next two questions are about the use of other 

tobacco products, not described in the previous sections.

36. Which of the following tobacco products have you 

ever tried, even just one time? (CHOOSE ALL 

THAT APPLY)

a. Smoking tobacco from a hookah or waterpipe

b. Pipe filled with tobacco (not waterpipe)

c. Snus, such as Camel or Marlboro Snus

d. Dissolvable tobacco products such as Ariva, 

Stonewall, Camel orbs, Camel sticks, Marlboro 

sticks or Camel strips

e. Bidis (small brown cigarettes wrapped in a leaf)

f. I have never tried any of the products listed 

above 

37. In the past 30 days, which of the following products 

have you used on at least one day? (CHOOSE ALL 

THAT APPLY)

a. Smoking tobacco from a hookah or waterpipe 

b. Pipe filled with tobacco (not waterpipe)

c. Snus, such as Camel or Marlboro

d. Dissolvable tobacco products, such as Ariva, 

Stonewall, Camel orbs, Camel sticks, or Camel 

strips 

e. Bidis (small brown cigarettes wrapped in a leaf)

f. I have not used any of the products listed above 

in the past 30 days

The next question asks about flavors in tobacco 

products.

38. Which of the following tobacco products that you 

used in the past 30 days were flavored to taste like 

menthol (mint), alcohol (wine, cognac), candy, fruit, 

chocolate or other sweets (CHOOSE ALL THAT 

APPLY)? 

a. Cigars, cigarillos, or little cigars

b. Chewing tobacco, snuff, or dip

c. Electronic cigarettes or e-cigarettes

d. Smoking tobacco out of a hookah or waterpipe

e. Pipe filled with tobacco (not waterpipe)

f. Snus

g. Dissolvable tobacco products

h. I did not use flavored tobacco products in the

past 30 days
Methodology Report: 2014 National Youth Tobacco Survey

A-7

The next question asks about the first tobacco product 

ever tried.

39. Which of the following tobacco products did you try 

first (CHOOSE ONLY ONE ANSWER)? 

a. Cigarettes

b. Cigars, cigarillos, or little cigars

c. Chewing tobacco, snuff, or dip

d. Electronic cigarettes or e-cigarettes

e. Some other tobacco product

f. Not sure about the product I tried first

g. I have never tried any tobacco products

The next four questions are about getting tobacco 

products.

40. During the past 30 days, how did you get your own 

tobacco products? (You can CHOOSE ONE 

ANSWER or MORE THAN ONE ANSWER) 

a. I did not get any tobacco products during the 

past 30 days

b. I bought them myself

c. I had someone else buy them for me

d. I asked someone to give me some

e. Someone offered them to me

f. I bought them from another person

g. I took them from a store or another person

h. I got them some other way 

41. During the past 30 days, where did you buy your 

own tobacco products? (You can CHOOSE ONE 

ANSWER or MORE THAN ONE ANSWER) 

a. I did not buy tobacco products during the past 

30 days

b. A gas station or convenience store

c. A grocery store

d. A drugstore

e. A vending machine

f. Over the Internet

g. Through the mail

h. Some other place not listed here 

42. During the past 30 days, did anyone refuse to sell 

you any tobacco products because of your age? 

a. I did not try to buy any tobacco products 

during the past 30 days

b. Yes

c. No

43. How easy do you think it is for kids your age to buy 

tobacco products in a store?

a. Easy

b. Somewhat easy

c. Not easy at all

The next four questions are about issues related to 

urges or needs to use tobacco products.

44. During the past 30 days, have you had a strong 

craving or felt like you really needed to use a 

tobacco product of any kind (such as smoking a 

cigarette or cigar, or using chewing tobacco)?

a. Yes

b. No

45. During the past 30 days, was there a time when 

you wanted to use a tobacco product so much that 

you found it difficult to think of anything else?

a. Yes

b. No

46. How soon after you wake up do you want to use a 

tobacco product?

a. I do not want to use tobacco

b. Within 5 minutes

c. From 6 to 30 minutes

d. From more than 30 minutes to 1 hour

e. After more than 1 hour but less than 24 hours

f. I rarely want to use tobacco

47. How true is this statement for you? I feel restless 

and irritable when I don’t use tobacco for a while.

a. I do not use tobacco

b. Not at all true

c. Sometimes true

d. Often true

e. Always true
Methodology Report: 2014 National Youth Tobacco Survey

A-8

The next four questions are about quitting tobacco 

products.

48. Are you seriously thinking about quitting 

cigarettes? (PLEASE CHOOSE THE FIRST

ANSWER THAT FITS)

a. I do not smoke cigarettes

b. Yes, within the next 30 days

c. Yes, within the next 6 months

d. Yes, within the next 12 months

e. Yes, but not within the next 12 months

f. No, I am not thinking about quitting cigarettes

49. During the past 12 months, how many times have 

you stopped smoking cigarettes for one day or 

longer because you were trying to quit smoking 

cigarettes for good?

a. I did not smoke cigarettes during the past 12 

months

b. I did not try to quit during the past 12 months

c. 1 time

d. 2 times

e. 3 to 5 times

f. 6 to 9 times

g. 10 or more times

50. Are you seriously thinking about quitting the use of 

all tobacco products? (PLEASE CHOOSE THE 

FIRST ANSWER THAT FITS)

a. I do not use tobacco products

b. Yes, within the next 30 days

c. Yes, within the next 6 months

d. Yes, within the next 12 months

e. Yes, but not within the next 12 months

f. No, I am not thinking about quitting the use of 

all tobacco products

51. During the past 12 months, how many times have 

you stopped using all tobacco products for one 

day or longer because you were trying to quit all 

tobacco products for good?

a. I did not use tobacco products during the past 

12 months

b. I did not try to quit all tobacco products during 

the past 12 months

c. 1 time

d. 2 times

e. 3 to 5 times

f. 6 to 9 times

g. 10 or more times

The next questions ask about your thoughts on tobacco 

products.

52. How much do you think people harm themselves 

when they smoke cigarettes some days but not 

every day?

a. No harm

b. Little harm

c. Some harm

d. A lot of harm

53. How much do you think people harm themselves 

when they smoke cigars, cigarillos or little cigars

some days but not every day?

a. No harm

b. Little harm

c. Some harm

d. A lot of harm

54. Do you believe that cigars, cigarillos, or little 

cigars are (LESS HARMFUL, EQUALLY 

HARMFUL, or MORE HARMFUL) than cigarettes?

a. Less harmful

b. Equally harmful

c. More harmful

d. I have never heard of cigars, little cigars or 

cigarillos

e. I don’t know enough about these products
Methodology Report: 2014 National Youth Tobacco Survey

A-9

55. Do you believe that cigars, cigarillos or little cigars

are (LESS ADDICTIVE, EQUALLY ADDICTIVE, or 

MORE ADDICTIVE) than cigarettes?

a. Less addictive

b. Equally addictive

c. More addictive

d. I have never heard of cigars, cigarillos, or little 

cigars

e. I don’t know enough about these products

56. How much do you think people harm themselves 

when they use chewing tobacco, snuff, dip, or 

snus, some days but not every day?

a. No harm

b. Little harm

c. Some harm

d. A lot of harm 

57. Do you believe that chewing tobacco, snuff, dip, or 

snus is (LESS HARMFUL, EQUALLY HARMFUL, or 

MORE HARMFUL) than cigarettes?

a. Less harmful

b. Equally harmful

c. More harmful

d. I have never heard of chewing tobacco, snuff, 

dip, or snus

e. I don’t know enough about these products 

58. Do you believe that chewing tobacco, snuff, dip or 

snus is (LESS ADDICTIVE, EQUALLY ADDICTIVE, 

or MORE ADDICTIVE) than cigarettes?

a. Less addictive

b. Equally addictive

c. More addictive

d. I have never heard of chewing tobacco, snuff, 

dip or snus

e. I don’t know enough about these products

59. How much do you think people harm themselves 

when they use e-cigarettes some days but not every 

day?

a. No harm

b. Little harm

c. Some harm

d. A lot of harm

60. Do you believe that e-cigarettes are (LESS 

HARMFUL, EQUALLY HARMFUL, or MORE 

HARMFUL) than regular cigarettes?

a. Less harmful

b. Equally harmful

c. More harmful

d. I have never heard of e-cigarettes

e. I don’t know enough about these products 

61. Do you believe that e-cigarettes are (LESS 

ADDICTIVE, EQUALLY ADDICTIVE, or MORE 

ADDICTIVE) than cigarettes?

a. Less addictive

b. Equally addictive

c. More addictive

d. I have never heard of e-cigarettes

e. I don’t know enough about these products

62. How strongly do you agree with the statement 

‘All tobacco products are dangerous’?

a. Strongly agree

b. Agree

c. Disagree

d. Strongly disagree

63. Do you think that breathing smoke from other 

people’s cigarettes or other tobacco products 

causes...

a. No harm

b. Little harm

c. Some harm

d. A lot of harm

The next ten questions ask about different issues 

related to tobacco.

64. When you are using the Internet, how often do 

you see ads or promotions for cigarettes or other 

tobacco products?

a. I do not use the Internet

b. Never

c. Rarely

d. Sometimes

e. Most of the time

f. Always 
Methodology Report: 2014 National Youth Tobacco Survey

A-10

65. When you read newspapers or magazines, how 

often do you see ads or promotions for cigarettes 

or other tobacco products?

a. I do not use read newspapers or magazines

b. Never

c. Rarely

d. Sometimes

e. Most of the time

f. Always 

66. When you go to a convenience store, supermarket, 

or gas station, how often do you see ads or 

promotions for cigarettes or other tobacco 

products?

a. I never go to a convenience store, 

supermarket, or gas station

b. Never

c. Rarely

d. Sometimes

e. Most of the time

f. Always 

67. When you watch TV or go to the movies, how often 

do you see actors and actresses using cigarettes 

or other tobacco products?

a. I do not watch TV or go to the movies

b. Never

c. Rarely

d. Sometimes

e. Most of the time

f. Always 

68. When you are using the Internet, how often do you 

see ads or promotions for electronic cigarettes or ecigarettes?

a. I do not use the Internet

b. Never

c. Rarely

d. Sometimes

e. Most of the time

f. Always 

69. When you read newspapers or magazines, how 

often do you see ads or promotions for electronic 

cigarettes or e-cigarettes?

a. I do not use read newspapers or magazines

b. Never

c. Rarely

d. Sometimes

e. Most of the time

f. Always 

70. When you go to a convenience store, supermarket, 

or gas station, how often do you see ads or 

promotions for electronic cigarettes or e-cigarettes?

a. I never go to a convenience store, 

supermarket, or gas station

b. Never

c. Rarely

d. Sometimes

e. Most of the time

f. Always 

71. When you watch TV or go to the movies, how often 

do you see ads or promotions for electronic 

cigarettes or e-cigarettes?

a. I do not watch TV or go to the movies

b. Never

c. Rarely

d. Sometimes

e. Most of the time

f. Always 

72. In the past 30 days, how often have you thought 

about the harmful chemicals in tobacco products?

a. Never

b. Rarely

c. Sometimes

d. Often

e. Very often
Methodology Report: 2014 National Youth Tobacco Survey

A-11

73. During the past 30 days, how often did you see a 

warning label on a smokeless tobacco product 

such as chewing tobacco, snuff, dip, or snus? 

a. I did not see a smokeless tobacco product 

during the past 30 days

b. Never 

c. Rarely

d. Sometimes

e. Most of the time

f. Always

The nex six questions ask about your thoughts on 

people your age who use cigarettes, cigars, smokeless 

tobacco and e-cigarettes

74. Do you think smoking cigarettes makes young 

people look cool or fit in?

a. Definitely yes

b. Probably yes

c. Probably not

d. Definitely not

75. Do you think young people who smoke cigarettes

have more friends?

a. Definitely yes

b. Probably yes

c. Probably not

d. Definitely not

76. Do you think smoking cigars, cigarillos or little 

cigars makes young people look cool or fit in?

a. Definitely yes

b. Probably yes

c. Probably not

d. Definitely not

77. Do you think young people who smoke cigars, 

cigarillos, or little cigars have more friends?

a. Definitely yes

b. Probably yes

c. Probably not

d. Definitely not

78. Do you think young people who use chewing 

tobacco, snuff, or dip have more friends?

a. Definitely yes

b. Probably yes

c. Probably not

d. Definitely not

79. Do you think young people who use electronic 

cigarettes or e-cigarettes have more friends?

a. Definitely yes

b. Probably yes

c. Probably not

d. Definitely not

The next question asks about your experiences at 

home.

80. Does anyone who lives with you now...? (CHECK 

ALL THAT APPLY).

a. Smoke cigarettes

b. Smoke cigars, cigarillos, or little cigars

c. Use chewing tobacco, snuff, or dip

d. Use electronic cigarettes or e-cigarettes

e. Smoke tobacco from a hookah or waterpipe

f. Smoke pipes filled with tobacco (not 

waterpipes)

g. Use snus

h. Use dissolvable tobacco products 

i. Smoke bidis (small brown cigarettes wrapped 

in a leaf)

j. No one who lives with me now uses any form 

of tobacco

Some cigarette or other tobacco companies make items 

like sports gear, T-shirts, hats, jackets, sunglasses or 

other items that people can buy or receive for free.

81. How likely is it that you would ever use or wear 

something--such as a t-shirt, hat, or sunglasses--that 

has a tobacco brand name, logo, or picture on it?

a. Very likely

b. Somewhat likely

c. Somewhat unlikely

d. Very unlikely
Appendix B

Student Weight Detail
Methodology Report: 2014 National Youth Tobacco Survey

B-1

APPENDIX B. STUDENT WEIGHT DETAIL

Students are selected from schools via the selection of intact class sections as described in Section 

2.2.4. The student sampling weight is computed based on a ratio of enrolling to responding 

students described in Section 4.2.1. The purpose of this section is to show that the resulting student 

weight is equivalent to computing a student weight as the inverse of the selection probability—are 

the other stage sampling weights—followed by two adjustments, one for nonresponse, and another 

poststratifying to known enrollment totals.

For the purposes of clarity, we omit the subscripts denoting the sampling stages and weight class. 

The unsubscripted quantities presented are assumed to be within weight class c, as defined in 

section 4.2.1.

The probability of selection of a class when there are Cjklm classes at grade j in school k, PSUi, 

stratum m is just 1/Cjklm or 2/Cjklm, depending on whether 1 or 2 classes are taken in the school. All 

students in a selected class were chosen so the probability of selection of a student is the same as 

the class, as well as constant across students within student weighting class. The initial selection 

probability is taken to be the inverse of this sampling probability.

In our simplified notation, letting K represent the number of sampled class sections, we have:

K

C W 

Nonresponse Adjustment

The nonresponse adjustment inflates the weight of the responding students to equal that of the 

sampled students. The adjustment is calculated as the sum of the weights for sampled students to 

the sum of the weights for responding students;

R

n

F  





Responding

Selected

NR W

W

where n represents the number of sampled students and R represents the number of responding 

students in the student weight class. Note that the equation simplifies to a ratio that does not involve 

W, as W is constant within the class.

Enrollment Ratio Adjustment

Next, the nonresponse adjusted student weights are ratio adjusted to conform to known school 

enrollment totals for each grade and sex. The adjustment Fps is computed as

R W

N

W

N

F

 









ps
Methodology Report: 2014 National Youth Tobacco Survey

B-2

where N is the number of enrolled students in the weight class, and 

W W FNR



 

The fully adjusted student weight is computed as:

W W FPS







Simplifying, we get

R

N

R W

N

W

W W FPS



 

 

  
Methodology Report: 2014 Youth Tobacco Survey

D-1
Appendix C

Common Core of Data 

Race/Ethnicity Definitions
APPENDIX C. COMMON CORE OF DATA RACE/ETHNICITY DEFINITIONS

Non-Hispanic American Indian/Alaska Native—A person having origins in any of the original 

peoples of North and South America (including Central America) and who maintains cultural 

identification through tribal affiliation or community recognition.

Non-Hispanic Asian/Pacific Islander—A person having origins in any of the original peoples of 

the Far East, Southeast Asia, the Indian subcontinent, or the Pacific Islands. This area includes, for 

example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, Thailand, Vietnam, Guam, 

the Philippine Islands, Samoa, and other Pacific Islands.

Non-Hispanic Black—A person having origins in any of the black racial groups of Africa; African 

American.

Hispanic—A person of Mexican, Puerto Rican, Cuban, Central or South American, or other 

Spanish culture or origin, regardless of race.

Non-Hispanic White—A person having origins in any of the original peoples of Europe, North 

Africa, or the Middle East.

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