2013 National Youth Tobacco Survey

METHODOLOGY REPORT

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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 2013 NYTS Methodology........................................................................................ 1

Chapter 2—NYTS Sampling Method..................................................................................................................... 3

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

2.1.1 Design Features for Minority Oversampling.............................................................................. 3

2.1.2 Sampling Stages and Measure of Size ................................................................................... 4

2.1.2 Stratification and Linking.................................................................................................................... 6

2.1.2.1 PSU ........................................................................................................................................ 6

2.1.3 Sample Sizes.......................................................................................................................... 9

2.1.3.1 Middle School and High School Estimates ......................................................................... 11

2.1.3.2 Grade Estimates................................................................................................................... 12

2.1.3.3 Gender Group Estimates...................................................................................................... 12

2.1.3.4 Racial Group Estimates........................................................................................................ 12

2.2 Sampling Methods............................................................................................................................. 12

2.2.1 PSU ...................................................................................................................................... 12

2.2.2 Schools................................................................................................................................. 13

2.2.3 Grades.................................................................................................................................. 14

2.2.4 Classes.................................................................................................................................. 15

Chapter 3—NYTS Data Collection ...................................................................................................................... 16

3.1 Survey Instrument ............................................................................................................................. 16

3.2 Recruitment Procedures .................................................................................................................... 16

3.3 Survey Administration ...................................................................................................................... 16

3.3.1 Data Collection Staffing ...................................................................................................... 16

3.3.2 Field Procedures................................................................................................................... 17

3.3.3 Classroom Selection............................................................................................................. 17

3.4 Participation Rates............................................................................................................................. 17

Chapter 4—Weighting of NYTS Response Data ................................................................................................. 19

4.1 Overview ........................................................................................................................................... 19

4.2 Sampling Weights ............................................................................................................................. 19

4.2.1 Adjusted Conditional Student Weights................................................................................ 19

4.2.2 School Sampling Weights.................................................................................................... 20

4.2.3 Grade Sampling Weights..................................................................................................... 20
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4.2.4 PSU Sampling Weights........................................................................................................ 20

4.2.5 Overall Sampling Weight .................................................................................................... 21

4.3 Non-Response Adjustments.............................................................................................................. 21

4.4 Weight Trimming.............................................................................................................................. 22

4.5 Post-Stratification to National Student Population Estimates........................................................... 24

4.6 Analysis Strata and Variance Estimation .......................................................................................... 28

Appendix A: Questionnaire .................................................................................................................................. 34

Appendix B: Student Weight Detail ................................................................................................................... 524

Appendix C: Common Core of Data Race/Ethnicity Definitions...................................................................... 554

List of Exhibits and Figure

Exhibit 2-1: Key Sampling Design Features .......................................................................................................... 5

Exhibit 2-2: Stratum Definition and PSU Allocation to Strata............................................................................... 8

Figure 2-1: Linked School Construction and Grade Sampling for High Schools .................................................. 8

Exhibit 2-3: Planned Sample Sizes for the 2013 NYTS....................................................................................... 10

Exhibit 3-1: Sample Yields for non-Hispanic Black and Hispanic Students by School Level ............................ 18

Exhibit 4-1: Double and Large School Non-Response......................................................................................... 23

Exhibit 4-2: Results of First Trimming Iteration .................................................................................................. 25

Exhibit 4-3: Counts by Schools and Students by Type and Eligibility Status...................................................... 29

Exhibit 4-4: Post-Stratification Adjustments........................................................................................................ 30

Exhibit 4-5: Sampling and Analysis Stratum Coding Schemes............................................................................ 32

Exhibit 4-6a: Current and Ever Use Estimates for High School Students............................................................ 32

Exhibit 4-6b: Current and Ever Use Estimates for Middle School Students........................................................ 33
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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 (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 pro-tobacco 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): TU-2, TU-3, TU-7, TU-11, TU-18 (including two sub-objectives:

TU-18.1 [internet advertising and promotion] and TU-18.2 [magazine and newspaper advertising and

promotion]), and TU-19.

First conducted during fall 1999 and again during spring 2000, 2002, 2004, 2006, 2009, 2011, 2012, and 2013,

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. 

1.2 Overview of the 2013 NYTS Methodology

The 2013 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. Non-Hispanic black and Hispanic

students were oversampled. Sampling procedures were probabilistic and conducted without replacement at all

stages, and entailed selection of: 1) Primary Sampling Units (PSUs) (a county, or a group of small counties, or

part of a very large county) within each created stratum; 2) schools within each selected PSU; and 3) students

within each selected school. Participating students completed the survey via pencil and paper using a selfadministered, 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 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 250 schools, of which 187 participated, yielding a school participation rate of

74.8%. A total of 18,406 student questionnaires were completed out of a sample of 20,301 students, yielding a

student participation rate of 90.7%. The overall participation rate, defined as the product of the school-level and

student-level participation rates, was 67.8%. 

 

1 CDC. Best Practices for comprehensive tobacco control programs-2014. Atlanta, GA: US Department of Health and

and Human Services, Public Health Service, CDC; 2014.

2 MacDonald G, Starr G, Schooley M, Yee SL, Klimowski K, Turner K. Introduction to program evaluation for 

comprehensive tobacco control programs. Atlanta, GA: US Department of Health and Human Services, CDC; 2001.
2

A weighting factor was applied to each student record to adjust for non-response and for varying probabilities

of selection. Weights were adjusted to ensure that the weighted proportions of students in each grade matched

national population proportions. Final adjusted weights were scaled to ensure that the weighted count of

students was equal to the total sample size.

The remainder of this report provides detailed information on the methodology used in the 2013 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 Method

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, Catholic, and other 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 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, such as cross-tabulations of grade by sex and of race/ethnicity by school level, were also

supported; however, precision levels will vary considerably according to differences in sub-population sizes.

The universe for the study consisted of all public, Catholic, and other 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 NYTS is a continuation of the NYTS cycles that took place in 1999, 2000, 2002, 2004, 2006, 2009, 2011, 

and 2012. The NYTS employs a repeat cross-sectional design to develop national estimates of tobacco use

behaviors and exposure to pro- and anti-tobacco influences among students enrolled in grades 6–12. The 

sampling design framework used for the 2012 NYTS was also employed for the 2013 NYTS; however, the 

development and implementation of the 2013 NYTS was coordinated with the 2013 Youth Risk Behavior 

Survey (YRBS) to avoid duplicative efforts and to minimize potential burden on school participants. 

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, and double class selection in high-minority schools. 

A weighted measure of size (MOS) has been used to increase the probability of selection of high racial/ethnic 

minority PSUs and schools within a Probability Proportional to Size (PPS) sampling design. The effectiveness 

of a weighted MOS in achieving oversampling is dependent upon the distributions of non-Hispanic black and 

Hispanic students in schools. The need for a weighted measure of size is predicated on a relatively low 

prevalence of minority students in the population; however, this premise has become less tenable with the 

increase of non-white students in the population overall, and specifically, Hispanic students.

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 this study has been updated with each cycle of the NYTS to ensure that the minimum amount of weighting 

 

3 Errecart, M.T., Issues in Sampling African-Americans and Hispanics in School-Based Surveys. Centers for Disease Control, 

October 5, 1990.
4

in the MOS is being used, while still achieving adequate representation of non-Hispanic black and Hispanic 

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

NYTS, with results demonstrating that adequate representation of non-Hispanic black and Hispanic students 

would be achieved through the use of an unweighted MOS. Thus, student enrollment was used as the 

unweighted MOS in the 2013 NYTS design, which also improved the statistical efficiency of the design.

Design parameters were examined to ensure that the precision and reliability of the data were not compromised 

by the employed sampling approach. Thresholds for double class selection were set, and PSUs were allocated to 

strata in the first sampling stage to generate adequate precision with minimum variance.

The need for oversampling Hispanic and non-Hispanic black students has been gradually reduced with the 

increasing numbers of minority populations in middle and high schools. Historically, the design has included

the following three different ways of oversampling Hispanic and non-Hispanic black students: 

 A weighted measure of size (described above)

 Disproportional allocation to strata with heavier concentrations of Hispanic and non-Hispanic black 

students

 Double class selection

In recent years, the growing percent of Hispanic students has eliminated the need for oversampling Hispanics.

The measure of size used in the 2013 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 2013 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 2013 NYTS, double class 

selection was only used in schools that had greater than 5 percent non-Hispanic black student enrollment. 

2.1.2 Sampling Stages and Measure of Size

The three-stage cluster sample was stratified by racial/ethnic composition, non-Hispanic black and Hispanic,

and urban versus non-urban status at the first (primary) stage. Primary Sampling Units (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.; otherwise, they were classified as

“non-urban.” 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.

The sampling stages may be summarized as follows:

 Selection of PSUs: Eighty-five PSUs were selected from sixteen strata, with probability proportional to the

total number of eligible students enrolled in all eligible schools located within a PSU.
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 Selection of Schools: At the second sampling stage, two double schools were selected from each PSU. An

additional 24 large schools and 20 small schools were selected from subsample PSUs. 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.

Schools were stratified into double, large, and small schools based on their ability to support two, one, or less

than one class selection per grade. In double schools, an average of 1.46 classes were selected per grade by

selecting 2 classes per grade in 46% of selected double schools and one class per grade in the remaining

schools. The double class sampling took place in 90 schools, with non-Hispanic black enrollments over the 

established 5% threshold.

The sampling approach utilized Probability Proportion to Size (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 measure of size was used also 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

summary of the sampling design features.

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

85

Urban vs. non-urban

(2 strata);

Minority concentration

(8 strata)

Aggregate school size in

target grades

2 Schools

219 school selections: 170 double

schools (2 per PSU), 194large

schools and 30 small schools

Small, large and double;

High-school vs. middleschool

Weighted enrollment

(increased for black,

Hispanic groups)

3

Classes/

students

1 or 2 classes per grade (2 per

grade in large high-minority

schools)

 

4 One of the ten PSUs sampled to contribute large schools did not contain a high school.
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2.2 Stratification and Linking

This section describes frame preparation steps for the selection of the first- and second-stage samples of PSUs

and schools. These steps include: combining counties into Primary Sampling Units; linking schools into

Secondary Sampling Units; and the stratification and allocation methods at each of these stages.

The basis for the sampling frame is a comprehensive database of U.S. schools and school districts that was

obtained from a commercial vendor. The school facility data are continuously updated with school contact

information, facility information, and openings and closings. The frame also incorporates enrollment data,

which serves as the basis for the measure of size used in the sampling. Enrollment data were obtained from the 

most recent Common Core of Data from the National Center for Education Statistics, which are continuously 

merged into the current school and school district data files of Quality Education Data, Inc. (formerly QED), 

acquired by MCH Strategic Data (http://www.mchdata.com/qed).

2.2.1 PSU

Defining a PSU

In defining PSUs, 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. There should be recent data available to characterize the PSUs.

4. PSU definitions should be consistent with secondary sampling unit (school) definitions

5. PSU should contain at least 4 middle and 5 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 probability one. Near-certainty 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 2013 NYTS PSU definitions were based on the definitions developed in the coordinated 2011 YRBSNYTS cycle, and also used in the 2012 NYTS. The exact PSUs defined in 2013 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.
7

Stratification of PSUs

The PSUs were organized into 16 strata, based on urban/non-urban location (as defined above) and racial/ethnic 

minority enrollment of non-Hispanic blacks and Hispanics. The approach involves the computation of optimum

stratum boundaries using the cumulative square root of “f” method developed by Dalenius and Hodges5. 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 “non-urban.”

 If the percentage of Hispanic students in the PSU exceeded the percentage of non-Hispanic black students,

then the PSU is classified as Hispanic. Otherwise it is classified as non-Hispanic black.

 Hispanic urban and Hispanic non-urban PSUs were classified into four density groupings depending upon

the percentages of Hispanics in the PSU.

 For urban, High Hispanic PSU, the percentage cut points used to define the groups were 24, 40, and 60

percent

 For non-urban, High Hispanic PSU, the percentage cut points used to define the groups were 24, 50, and 

68 percent.

 Non-Hispanic Black urban and non-Hispanic black non-urban PSUs were also classified into four 

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

 For urban non-Hispanic black PSUs, the percentage cut points used to define the groups were 26, 36,

and 54 percent.

 For non-urban High non-Hispanic Black PSUs, the percentage cut points used to define the groups were 

20, 36, and 58 percent.

Allocation of the PSU Sample

We designed and selected a sample of 85 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 strata would 

have at least two sampled PSUs, and to add 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.

 

5 Dalenius, T, and Hodges, JL (1959) Minimum Variance Stratification. Jour. Amer. Statist. Assoc., 54, 88-101.
8

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

Predominant 

Minority

Urban/Nonurban 

Density 

Group 

Number

Stratum 

Code

Student 

Population

Percent of 

Student 

Population

Number 

of 

Sample 

PSUs

Non-Hispanic 

Black

Urban 1 BU1 2,527,334 9% 8

2 BU2 1,773,146 6% 5

3 BU3 888,683 3% 2

4 BU4 518,266 2% 2

Non-urban 1 BR1 3,942,092 14% 11

2 BR2 1,947,857 7% 6

3 BR3 1,108,460 4% 3

4 BR4 399,673 1% 1

Hispanic Urban 1 HU1 3,193,712 11% 10

2 HU2 2,182,920 8% 7

3 HU3 2,218,898 8% 6

4 HU4 1,372,469 5% 4

Non-urban 1 HR1 4,016,186 14% 12

2 HR2 1,137,313 4% 3

3 HR3 850,159 3% 3

4 HR4 500,907 2% 2

2.2.2 Schools

Linking into Secondary 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 OID A’ is linked

with ’Component School OID B’, to form a linked 

school, or ‘Secondary Sampling Unit (SSU) XXX’. 

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 a single school, or sampling

unit, during sampling with selection performed at

the grade level as described below.

Figure 2-1: Linked School Construction and Grade 

Sampling for High Schools
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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 were also stratified by school size into ‘small’, ‘large’, and ‘double’ based on their ability to support less

than one, one, or two class selection per grade. Operationally, double SSUs contained at least 50 students at

each grade level, large SSU contained between 25 and 49 students per grade, and small SSUs contained less

than 25 students at any grade level.

It is important to note that the nomenclature used to describe school size stratification has been slightly modified 

for this cycle. Schools are now classified by enrollment size as ‘small’, ‘large’, or ‘double’. The change in 

nomenclature was done to distinguish the schools where double class sampling would take place.

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 the key

estimates accurate to within ± 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 to within ± 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,

etc.), and by individual grade (6th grade males, 6

th grade females, etc.)

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

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. For the 2013 NYTS design, anticipated precision levels

were developed to ensure that the 2013 design meets the original precision targets. The sample design proposed 

for the 2013 NYTS survey is consistent with the sample design used in past cycles, which includes adjusting 

sampling parameters to reflect changing demographics of the in-school population of middle and high school 

students. The number of schools selected and students per school were calculated so that, combined with

anticipated response rates, we projected the study would obtain completed surveys from approximately 21,379

students.
10

As detailed in Section 2.2.2, linked schools, or second stage units (SSUs), were constructed to contain a full

complement of grades—6 to 8 for middle schools and 9 to 12 for high schools.

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 2-3.

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 “Double”, and those among the others with 28 

students per grade are considered “Large”; otherwise, they are considered “Small.”

 On average, each selected class will include 28 students (based on historical averages).

 For SSUs classified as Double schools, we will 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, 85 PSUs were selected. Within each PSU, two double schools were drawn, one at 

the middle school level to supply students in grades 6 through 8, and one at the high school level to supply 

students in grades 9 through 12. In addition, 15 PSUs were sub-sampled to supply small SSUs, and another 10 

PSUs were independently sub-sampled to supply large SSUs.

The number of students selected from all sample schools will be about 27,789 students (before non-response).

Exhibit 2-3 summarizes the designed sample sizes for each school type. This table details the number of schools

that were specified to be drawn by the sample design along with the number of participating schools and

students anticipated when we developed the sample design based on the given assumptions. Section 3.4

compares these projections to the actual sample yields.

In this exhibit, the schools are secondary sampling units (SSUs); SSUs are “virtual schools” created by combining 

actual, physical schools so that each virtual school unit has a complete set of grades for the level. The virtual 

schools will be expanded to physical schools.

Across the seven previous cycles of the NYTS (prior to the 2012 survey not yet completed at the time of this design 

work), the school participation has averaged 90%, with a low of 83%. Student participation has averaged 91% with 

a low of 88%. In calculating the drawn sample sizes for the 2013 NYTS, we made our approach more robust by 

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

82%. 

Exhibit 2-3: Planned Sample Sizes for the 2013 NYTS
11

PSU SSU

Sampled 

students

prior to 

attrition

Sample size calculation

Overall yields at

77% overall 

response rate

85

Double High 

School 85 13,899

8,758 in 39 double schools (39 schools x 8 classes per 

school x 28 students per class)

5,141 in 46 non-double schools (46 schools x 4 classes 

per school x 28 students per class)

Double 

Middle 

School

85 10,424

6,569 students in 39 double schools (39 schools x 6 

classes per school x 28 students per class)

3,856 students in 46 non-doubled schools (46 schools x 

3 classes per school x

28 students per class)

Double Total 170 24,324 18,729

10

(subsample)

Large High 

School 10 1,120 10 PSU x 1 school per PSU x 28 kids per grade x 4 grades at the HS level

Large Middle 

School 10 840 10 PSU x 1 school per PSU x 28 kids per grade x 3 grades at the MS level

Large Total 20 1,960 1,509

15

(subsample)Small 30 1,505

1,030 High School students (averages of 18.1 students 

per class and 57 classes, with 3.8 classes per school)

475 Middle School students (averages of 11.2 students 

per class and 42 classes, with 2.8 classes per school)

1,159

Overall Total 220 27,789 21,397

In summary, the design anticipated that between 235 and 245 physical schools would be selected for participation 

in the 2013 NYTS, a number inflated due to school non-response, as well as from the linking of physical schools 

into SSUs. These schools were expected to yield approximately 21,397 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%. 

Because the design expected to yield a greater number of completed surveys from high school students than

from middle school students, overall estimates were anticipated to be more precise at the high school level than

those at the middle school level. Moreover, because within grade estimates by sex have slightly larger standard

errors than those for estimates by grade alone, estimates of sex were expected within ± 5%.

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

school level, grade, sex and race/ethnicity.

2.2.3.1 Middle School and High School Estimates
12

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, 9

th 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 design balances the sample sizes for grade level by targeting 3,000 students per grade. This ensures that

estimates at the grade level achieve the required precision levels. It is worth noting that this design feature

resulted in a larger student allocation to the high school stratum than to the middle school stratum because high

schools have four grades, compared to three grades for middle schools.

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 designed 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 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
13

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 probability proportional to size (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 100 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 12 of the sample PSUs for the medium school sample for each school level (middle

school and high school)

 Subsample at random 10 of the sample PSUs for the small school sample for each school level (middle

school and high school)

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 P

p

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













MOS

MOS

P = K

..m

.lm

m

P

lm

As noted below, 10 of the 100 sample PSUs were sub-sampled for the sampling of small schools, with 5 PSUs

sub-sampled for each school level. Similarly, 12 PSUs were sub-sampled for the sampling of large schools, with

6 for each school level. Thus, the sub-sample PSUs have an additional factor in their selection probability for 

these classes of schools. This factor is incorporated into the school sampling probability below because it is 

more closely associated with school selection. 

2.3.2 Schools

Selection

For ‘double’ 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 weighted measure

of size.

‘Small’ and ‘large’ schools were sampled independently from ‘double’ schools; they were set in two separate

strata sampled at lower rates. This approach was implemented by drawing a sub-sample of 15 PSUs for the

sampling of ‘small’ schools sampling and a subsample of 10 PSUs for ‘large’ school sampling at each level. 

One ‘small’ school or ‘large’ school was then selected in each sub-sampled PSU with probability proportional

to weighted measure of size.

Replacement of Schools/School Systems
14

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

non-response by inflating the sample sizes to account for non-response. 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 ‘double’ school k in PSU l and stratum m, P

DS

klm, at each level was computed as

follows:













MOS

MOS

P =

.lm

DS klm

klm

For ‘small’ schools, one school was drawn from sub-sampled PSU at each level, so the probability of selection

of a ‘small’ school, P

SS

klm, then becomes:

  











MOS

MOS

P =

.lm

SS klm

klm 10/100

For ‘large’ schools, one school was drawn from sub-sampled PSU, so the probability of selection of a ‘large’

school at each level, P

LS

klm, then becomes:

  











MOS

MOS

P =

.lm

LS klm

klm 12 /100

Note the additional sampling factor in the probability of selection for ‘small’ and ‘large’ schools is due to the 

PSU sub-sampling for these classes of schools as noted above.

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 P

G

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
15

2.3.4 Classes

Selection

In ‘double’ schools, an average of 1.46 classes per grade were selected by selecting 2 classes per grade in 46% 

of the selected ‘double’ schools and one class per grade in the remaining ‘double’ schools. The double class

sampling took place in schools with greater than 5% non-Hispanic black enrollment and one class per grade in

the remaining schools.

One class per grade was selected in ‘large’ 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.

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 5%, 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 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 (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 P

C

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 P

C

ijklm.
16

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 2013 survey instrument included a total of 81 questions, with the first five 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 towards tobacco use; pro- and anti-tobacco 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 2013 NYTS were located in 39 different states. Recruitment began in

May 2012 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 12, 2013, immediately after data collector training, and

continued until June 21, 2013. Each data collector visited an average of 3 schools per week. While the details of

each data collection varied, there were six core steps followed for every school: 1) Pre-contact 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)

Post-survey meeting with the teacher or teachers; and 6) Post-survey meeting with the principal or lead contact

prior to leaving the school. Most survey administrations could be completed in one 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 6 – 9, 2013. Key components of the training included:

 Precontact activities with the schools

 Entry and exit meetings with school officials

 Data collection protocols

 Follow up activities

 Communication with headquarters staff
17

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 pre-survey 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 one 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 two 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. 

3.4 Participation Rates

Across the eight previous cycles of the NYTS, the school participation has averaged 88%, with a low of 83%. 

Student participation has averaged 90% with a low of 88%, and the overall response rate has averaged 81%. To

be conservative, we assumed slightly lower values in developing the sample design for the 2013 NYTS: an

assumed overall participation rate of 77%.

The actual response rates differed from our projections: an actual school participation rate of 74.8% and a

student participation rate of 90.7%. These participation rates were lower for schools but higher for student

participation. The overall participation rate, the product of the school-level and student-level participation rates

was 67.8%
18

The 2013 NYTS data file contains responses from 18,406 students compared to the 21,397 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 202 and 451 students for high and middle schools, respectively. Among Hispanics, a 

yield of 500 over target was observed among high school students but a shortfall of 76 was seen among middle 

school students.

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

Subgroup

Projected

Participants Actual Participants

Middle School nonHispanic Blacks 1,775 1,324

Middle School Hispanics 1,775 1,699

High School non-Hispanic 

Blacks 1,975 1,773

High School Hispanics 1,975 2,482
19

Chapter 4—Weighting of NYTS Response Data

4.1 Overview

This section describes the procedures used to weight the data collected in NYTS 2013. The process involved the

steps outlined below:

 Sampling weights

 Non-response adjustments

 Weight trimming

 Post-stratification to national estimates of racial totals by grade, gender 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 non-response patterns, to

mitigate large variations in sampling weights, and to post-stratify the data to known sampling frame

characteristics.

4.2 Sampling Weights

The sampling weight attached to each student response is the inverse of the probability of selection for that

student. This basic weight can be adjusted to compensate for non-response, to alleviate excess weight variation,

and to match the weighted data to known control totals. A convenient way of computing the basic weight is by

inverting the probabilities of selection at each stage, to derive a partial weight or stage weight. The stage

weights are then multiplied together to form the overall weight.

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, a non-response adjustment, and a ratio

adjustment to control to known school enrollment totals. 

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 weight class within a school. The 

weighting class definition is set dynamically so as to avoid extreme weights.

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 weight computation class, described below. This 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 weight class c within 

a given school:

R

N

W =

cklm

R cklm

cklm
20

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 

school.

Initially the weight class is defined by grade and gender within each school. We then combine weight classes if the

weight for the class exceeds a maximum value. This cap C is computed using the equation following.

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 weight class.

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

enrollment of less than 10, and 20% of the enrollment in weight classes with an enrollment of more than 10 but the 

cap could be exceeded in cases where the weight class is collapsed to the school level.

4.2.2 School Sampling Weights

For ‘double’ 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 =

DS

klm klm

DS .lm

klm 











For ‘small’ schools the partial school weight is:

P

1

=

MOS

MOS

W =

SS

klm klm

SS .lm

klm 











(85/15)

For ‘large’ schools the partial school weight is:

P

1

=

MOS

MOS

W =

LS

klm klm

LS .lm

klm 











(85/10)

4.2.3 Grade Sampling Weights

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. 

4.2.4 PSU Sampling Weights

The weight of the PSU is the inverse of the probability of selection of that PSU:
21

P

1

=

MOS

MOS

K

1

W =

P

lm lm

.m

m

P

lm 











For ‘small’ and ‘large’ school selections, the enclosing PSU were drawn as a subsample. 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 non-response, trimmed, and post-stratified 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

LS

klm

P

lm

T1

hijklm

R

hijklm

G

jklm

DS

klm

P

lm

T1

hijklm

for ‘double’, ‘large’, and ‘small’ schools, respectively, where the weights in the latter portions of the equations are 

defined in the preceding sections.

4.3 Non-Response 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 large and double 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

D S LS

klm

D S LS

klm

P

l m

k,l responding

D S LS

klm

D S LS

klm

P

l m

D S LS k,l

m

W W MOS

W W MOS

A =

W W MOS

W W MOS

A =

smallschools withrespondents

smallschoolssampled

, ,

doubleand large,schools

, ,

,

doubleand large,schoolssampled









The first equation applies to ‘double’ and ‘large’ schools combined, and the second applies to ‘small’ schools. 

Note that this adjustment is made within stratum for ‘double’ and ‘large’ schools and across the whole sample 

for ‘small’ schools.

 

The student weight, adjusted for non-response, is A

SS

lm WT1hijklm for ‘small’ schools and 

A

DS,LS

lm WT1hijklm for ‘double’ and ‘large’ schools.

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 non-response 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
22

HR4. School response rates by weighting class, and the resulting non-response adjustment factors, are detailed in

Exhibit 4-1. Note that the weighting classes are defined using collapsed sampling strata.

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.

 

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 non-response 

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.
23

Exhibit 4-1: Double and Large School Non-Response

School 

Level

Stratum (NonResponse)Sampled 

Schools

Responding 

Schools

Percent 

Responding

NonResponse 

Adjustment

HS BR1 13 11 84.62% 1.2

HS BR2 7 7 100.0% 1.0

HS BR3 and BR4 4 4 100.0% 1.0

HS BU1 12 11 91.67% 1.1

HS BU2 7 6 85.71% 1.0

HS BU3 and BU4 5 5 100.0% 1.0

HS HR1 14 10 71.43% 1.6

HS HR2 4 4 100.0% 1.0

HS HR3 and HR4 5 2 40.00% 2.3

HS HU1 10 7 70.00% 1.3

HS HU2 8 5 62.50% 1.7

HS HU3 and HU4 13 7 53.85% 1.7

HS Total 102 79 77.45% .

MS BR1 15 12 80.00% 1.2

MS BR2 8 8 100.0% 1.0

MS BR3 and BR4 5 5 100.0% 1.0

MS BU1 13 10 76.92% 1.9

MS BU2 7 6 85.71% 1.1

MS BU3 and BU4 5 5 100.0% 1.0

MS HR1 15 14 93.33% 1.0

MS HR2 4 3 75.00% 1.3

MS HR3 and HR4 8 4 50.00% 2.4

MS HU1 13 11 84.62% 1.2

MS HU2 11 6 54.55% 1.8

MS HU3 and HU4 12 8 66.67% 1.4

MS Total 116 92 79.31% .

Gross Total 218 171 78.44% .
24

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 will be

trimmed in the first iteration of the trimming algorithm.

The results of the first iteration of the trimming operation are summarized in Exhibit 4-2.

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 zero 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

4.5 Post-Stratification to National Student Population Estimates

To obtain accurate counts of high school students in schools considered eligible for the NYTS by sex, gender, 

and race/ethnicity for use in post-stratification, we turned to two school universe surveys conducted by the 

National Center for Education Statistics (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 the two sources: 1) Private schools 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 the Common Core of Data 

(CCD), both produced by the National Center for Education Statistics (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 

post-stratification step.

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

Common Core of Data (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 Private School Universe Survey (PSS), 

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

 

8 Common Core of Data, National Center for Education Statistics http://nces.ed.gov/ccd/. School Year 2010–11.
25

Exhibit 4-2: Results of First Trimming Iteration

Trimming 

Class

Number 

Cases

Trimming 

Factor

Total 

Weight

Percent 

Trimmed

CV After 

Trimming

CV Before 

Trimming

Design Effect 

After Trimming

Design Effect 

Before Trimming

NYTSBR106 295 3.5 447481.07 4.93905 41.507 57.171 1.17170 1.32574

NYTSBR107 305 1.8 453640.52 4.86141 38.638 48.174 1.14880 1.23131

NYTSBR108 297 1.9 422562.50 4.62490 36.189 47.362 1.13052 1.22356

NYTSBR109 322 3.4 528243.82 4.95334 48.550 64.697 1.23498 1.41727

NYTSBR110 296 2.5 447149.67 4.90142 35.104 51.049 1.12281 1.25971

NYTSBR111 311 2.4 402594.35 4.92091 48.270 57.769 1.23225 1.33265

NYTSBR112 243 2.2 345891.00 4.49907 41.993 51.367 1.17561 1.26277

NYTSBR206 287 9.1 378874.68 4.92259 153.957 165.999 3.36203 3.74596

NYTSBR207 274 9.8 339888.80 4.79306 138.979 157.527 2.92446 3.47242

NYTSBR208 271 6.6 294789.27 4.97879 118.854 130.306 2.40742 2.69170

NYTSBR209 231 2.2 312006.68 4.59582 39.880 49.591 1.15835 1.24486

NYTSBR210 263 1.9 276665.22 4.52269 36.264 44.708 1.13101 1.19912

NYTSBR211 214 2.4 272512.01 4.37229 39.006 49.338 1.15143 1.24228

NYTSBR212 257 3.1 257677.97 4.84595 45.128 58.752 1.20286 1.34384

NYTSBR306 132 1.7 88362.57 4.95680 45.977 52.224 1.20978 1.27067

NYTSBR307 128 1.2 94662.04 4.98980 24.328 29.192 1.05872 1.08455

NYTSBR308 137 1.3 83312.73 4.47106 27.771 33.702 1.07656 1.11276

NYTSBR309 120 1.7 156587.04 4.23676 38.559 44.200 1.14744 1.19374

NYTSBR310 140 1.4 145487.41 3.87328 29.038 33.650 1.08372 1.11242

NYTSBR311 69 1.0 122242.07 3.93577 5.115 9.929 1.00258 1.00971

NYTSBR312 105 3.0 117990.10 4.94038 44.826 57.691 1.19903 1.32965

NYTSBR406 33 1.0 18426.57 2.06997 0.094 4.300 1.00000 1.00179

NYTSBR407 32 1.6 20485.40 3.35425 28.568 35.507 1.07906 1.12213

NYTSBR408 46 1.1 20691.28 3.94160 5.369 13.369 1.00282 1.01749

NYTSBR409 41 1.1 112062.68 2.96812 5.197 11.223 1.00263 1.01229

NYTSBR410 44 1.0 107873.42 4.48909 0.427 9.518 1.00002 1.00885

NYTSBR411 31 1.4 100542.22 4.12915 16.535 25.308 1.02646 1.06198

NYTSBR412 41 1.4 72788.38 3.34374 18.803 25.674 1.03449 1.06431

NYTSBU106 277 8.1 465586.36 4.84087 94.116 112.556 1.88259 2.26231

NYTSBU107 305 7.5 609478.63 4.87309 81.793 100.016 1.66681 1.99704

NYTSBU108 304 7.0 610790.88 4.99476 83.509 101.324 1.69509 2.02327

NYTSBU109 305 2.7 388975.39 4.70123 39.987 51.766 1.15937 1.26710

NYTSBU110 303 1.8 430392.50 4.61179 33.972 43.592 1.11503 1.18940
26

Trimming 

Class

Number 

Cases

Trimming 

Factor

Total 

Weight

Percent 

Trimmed

CV After 

Trimming

CV Before 

Trimming

Design Effect 

After Trimming

Design Effect 

Before Trimming

NYTSBU111 333 3.5 433237.70 4.89635 33.350 54.257 1.11089 1.29350

NYTSBU112 321 1.9 407330.23 4.75893 32.080 45.150 1.10259 1.20321

NYTSBU206 180 1.9 170455.08 4.89767 51.744 57.487 1.26626 1.32863

NYTSBU207 219 1.7 207088.66 4.40678 30.287 38.237 1.09131 1.14554

NYTSBU208 195 2.0 205969.89 4.99840 31.083 42.732 1.09612 1.18167

NYTSBU209 239 2.5 293982.64 4.71863 41.988 54.272 1.17556 1.29331

NYTSBU210 217 3.1 326680.47 4.85937 57.218 67.879 1.32589 1.45863

NYTSBU211 198 3.9 280481.42 4.80823 71.534 82.883 1.50912 1.68349

NYTSBU212 210 3.3 299539.66 4.82555 66.381 77.745 1.43855 1.60155

NYTSBU306 111 0.9 96389.19 4.96455 0.000 5.965 1.00000 1.00353

NYTSBU307 120 1.4 99598.43 4.69482 16.361 27.572 1.02654 1.07539

NYTSBU308 125 1.1 99232.79 4.19434 10.536 18.581 1.01101 1.03425

NYTSBU309 62 3.0 119100.17 4.82684 63.050 74.651 1.39112 1.54829

NYTSBU310 108 1.2 117458.24 4.16849 18.282 23.697 1.03311 1.05564

NYTSBU311 104 2.3 112990.29 4.65428 27.709 40.358 1.07604 1.16131

NYTSBU312 101 1.3 102989.43 4.37938 11.972 20.868 1.01419 1.04312

NYTSBU406 110 3.5 114963.28 4.60920 55.116 67.557 1.30102 1.45224

NYTSBU407 107 3.7 106666.83 4.69011 76.352 88.168 1.57751 1.77009

NYTSBU408 113 3.7 110932.61 4.86101 77.865 89.700 1.60093 1.79749

NYTSBU409 124 4.3 284838.97 4.99812 74.810 86.568 1.55515 1.74335

NYTSBU410 118 3.0 197496.79 4.68550 61.128 70.238 1.37049 1.48916

NYTSBU411 114 6.0 188641.82 4.93066 65.738 83.170 1.42836 1.68567

NYTSBU412 96 1.8 185081.07 4.22843 38.508 46.505 1.14674 1.21402

NYTSHR106 350 11.5 542658.34 4.99023 80.358 106.357 1.64389 2.12795

NYTSHR107 372 6.5 778509.43 4.90948 105.553 119.292 2.11116 2.41924

NYTSHR108 407 6.7 810574.50 4.98145 103.863 117.515 2.07610 2.37758

NYTSHR109 296 4.7 860581.87 4.97057 67.407 81.178 1.45284 1.65675

NYTSHR110 244 4.0 777953.46 4.74869 64.263 76.029 1.41128 1.57568

NYTSHR111 286 4.7 773182.96 4.83612 79.961 92.641 1.63713 1.85524

NYTSHR112 271 6.3 740195.62 4.82254 91.815 105.606 1.83990 2.11114

NYTSHR206 81 1.4 160454.86 3.83425 37.585 41.628 1.13952 1.17115

NYTSHR207 74 2.6 152035.78 4.89045 59.175 68.528 1.34544 1.46326

NYTSHR208 86 1.5 153657.36 3.98703 31.267 37.388 1.09662 1.13816

NYTSHR209 109 7.3 177196.54 4.89985 84.469 101.410 1.70696 2.01896
27

Trimming 

Class

Number 

Cases

Trimming 

Factor

Total 

Weight

Percent 

Trimmed

CV After 

Trimming

CV Before 

Trimming

Design Effect 

After Trimming

Design Effect 

Before Trimming

NYTSHR210 117 2.6 153788.71 4.71771 46.718 56.336 1.21640 1.31467

NYTSHR211 114 4.6 151201.08 4.95607 54.959 70.992 1.29940 1.49957

NYTSHR212 91 2.2 162068.80 4.77002 36.518 47.152 1.13189 1.21988

NYTSHR306 67 2.0 114494.63 4.45946 71.805 75.886 1.50791 1.56727

NYTSHR307 65 1.1 143613.91 4.73569 9.829 18.776 1.00951 1.03471

NYTSHR308 58 2.5 141203.86 4.88242 25.555 41.124 1.06418 1.16620

NYTSHR309 75 1.2 179024.22 4.91809 29.999 33.784 1.08880 1.11261

NYTSHR310 62 1.2 168282.85 3.22903 25.134 27.615 1.06215 1.07503

NYTSHR311 61 1.4 163936.78 3.70246 21.687 28.062 1.04626 1.07746

NYTSHR312 66 1.7 132079.97 4.40938 29.908 39.153 1.08809 1.15097

NYTSHU106 291 3.2 389447.17 4.92335 77.355 86.826 1.59632 1.75128

NYTSHU107 303 2.4 387874.41 4.41909 46.640 56.400 1.21682 1.31704

NYTSHU108 315 2.7 419695.37 4.98435 56.645 66.569 1.31984 1.44173

NYTSHU109 283 4.1 554990.72 4.99516 52.804 67.743 1.27784 1.45729

NYTSHU110 252 9.9 556908.22 4.95873 86.303 107.732 1.74187 2.15601

NYTSHU111 261 3.1 535690.01 4.83888 58.210 68.625 1.33755 1.46913

NYTSHU112 328 5.7 518041.03 4.90861 82.821 97.500 1.68384 1.94773

NYTSHU206 165 3.7 306924.04 4.94595 61.920 74.984 1.38109 1.55886

NYTSHU207 160 2.9 323626.97 4.49575 62.330 71.378 1.38608 1.50630

NYTSHU208 191 3.5 343202.36 4.73265 55.219 67.103 1.30332 1.44793

NYTSHU209 213 3.5 286535.26 4.89854 48.189 64.335 1.23112 1.41196

NYTSHU210 163 2.1 269072.69 4.71359 46.793 54.297 1.21761 1.29301

NYTSHU211 147 2.0 234489.36 4.88992 47.611 54.423 1.22513 1.29417

NYTSHU212 144 1.7 235247.61 4.07867 31.409 39.963 1.09797 1.15860

NYTSHU306 169 1.9 382498.05 4.49130 40.847 49.457 1.16586 1.24315

NYTSHU307 185 2.5 353551.24 4.50185 45.792 55.555 1.20856 1.30697

NYTSHU308 157 1.3 353285.02 4.79226 28.530 36.073 1.08088 1.12930

NYTSHU309 162 3.5 478547.10 4.99012 50.863 66.126 1.25711 1.43457

NYTSHU310 176 3.1 435061.08 4.87250 47.842 61.779 1.22759 1.37949

NYTSHU311 184 2.7 429172.73 4.92075 52.308 63.241 1.27212 1.39776

NYTSHU312 138 1.5 431928.90 4.66080 25.708 33.643 1.06561 1.11237

NYTSHU406 81 2.9 91503.64 4.72086 50.227 60.509 1.24916 1.36161

NYTSHU407 69 1.7 170202.63 4.28631 36.034 42.473 1.12797 1.17778

NYTSHU408 95 1.5 158107.10 4.71080 30.603 40.818 1.09267 1.16486
28

Trimming 

Class

Number 

Cases

Trimming 

Factor

Total 

Weight

Percent 

Trimmed

CV After 

Trimming

CV Before 

Trimming

Design Effect 

After Trimming

Design Effect 

Before Trimming

NYTSHU409 56 1.5 249870.27 3.96146 38.942 42.715 1.14894 1.17920

NYTSHU410 106 1.1 160619.39 4.89585 8.379 20.422 1.00695 1.04131

NYTSHU411 93 4.0 221730.10 4.93640 86.297 95.607 1.73670 1.90425

NYTSHU412 83 2.6 223764.76 4.94607 67.326 74.382 1.44781 1.54660

Exhibit 4-3 gives counts of schools and students by grade for public and non-public schools based on both the

raw file and the resulting set of eligible schools. The latter set of student totals was used as control totals for the

post-stratification adjustments described next.

Given a national estimate of student counts Ra and a weighted response total of Pa for post-stratification adjustment 

class “a”, the post-stratification factor was the ratio of Ra to Pa. Exhibit 4-4 gives the population control totals used 

in post-stratification adjustments alongside the sum of the weights in each post-stratum 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.

Post-stratification 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 gender were 

not available for these schools. This is indicated by a “Combined” sex in Exhibit 4-4. 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; nonHispanic Asian/ Pacific Islander; and non-Hispanic Native American/Alaska Native (Appendix C).

Following post-stratification, the adjusted weights sum to the control population 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 2013 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). 
29

Exhibit 4-3: Counts by Schools and Students by Type and Eligibility Status

Raw (all) Eligible

Type Grade Schools Students Schools Students

Public 6 3,583 26,343 35,066 3,692,775

7 4,054 31,941 27,558 3,683,938

8 4,409 40,873 27,612 3,654,784

9 6,412 122,896 20,680 3,907,060

10 6,838 138,885 19,457 3,679,427

11 6,923 160,170 19,167 3,392,630

12 6,828 216,708 18,988 3,259,344

Total 39,047 737,816 168,528 25,269,958

Private 6 2,178 20,049 15,355 306,460

7 2,054 19,233 14,553 305,170

8 2,125 20,517 14,334 305,489

9 1,797 22,450 6,922 281,606

10 1,745 23,017 6,572 279,592

11 1,678 22,603 6,281 275,027

12 1,599 22,462 6,167 271,152

Total 13,176 150,331 70,184 2,024,496

Total 6 5,761 46,392 50,421 3,999,235

7 6,108 51,174 42,111 3,989,108

8 6,534 61,390 41,946 3,960,273

9 8,209 145,346 27,602 4,188,666

10 8,583 161,902 26,029 3,959,019

11 8,601 182,773 25,448 3,667,657

12 8,427 239,170 25,155 3,530,496

Total 52,223 888,147 238,712 27,294,454
30

Exhibit 4-4: Post-Stratification Adjustments

School 

Type Grade Race/Hispanic Origin Gender

(E) 

Control 

Total

(F) Weighted 

Estimate

No. of 

Cases

(G) PostStratification 

Adjustment

Private 6 Combined Combined 296,239 194,662 127 1.52181

Private 7 Combined Combined 294,840 243,240 184 1.21214

Private 8 Combined Combined 295,191 240,776 189 1.22600

Private 9 Combined Combined 272,669 442,066 304 0.61681

Private 10 Combined Combined 270,774 476,136 303 0.56869

Private 11 Combined Combined 266,308 482,118 330 0.55237

Private 12 Combined Combined 262,611 465,957 265 0.56360

Public 6 Non-Hispanic Asian and 

Pacific Islander

Female 83,993 108,844 77 0.77169

Public 6 Non-Hispanic Black Female 293,043 297,818 219 0.98396

Public 6 Hispanic Female 437,910 409,250 263 1.07003

Public 6 Non-Hispanic Native American Female 22,815 44,383 37 0.51404

Public 6 Non-Hispanic White Female 961,220 915,914 629 1.04946

Public 6 Non-Hispanic Asian and 

Pacific Islander

Male 86,306 117,396 81 0.73517

Public 6 Non-Hispanic Black Male 305,483 284,274 221 1.07461

Public 6 Hispanic Male 456,836 409,335 296 1.11604

Public 6 Non-Hispanic Native American Male 23,708 77,014 53 0.30784

Public 6 Non-Hispanic White Male 1,021,460 909,629 626 1.12294

Public 7 Non-Hispanic Asian and 

Pacific Islander

Female 82,961 134,238 90 0.61801

Public 7 Non-Hispanic Black Female 292,644 307,946 237 0.95031

Public 7 Hispanic Female 430,449 458,216 288 0.93940

Public 7 Non-Hispanic Native American Female 22,838 98,680 58 0.23144

Public 7 Non-Hispanic White Female 968,116 925,957 610 1.04553

Public 7 Non-Hispanic Asian and 

Pacific Islander

Male 86,022 107,616 58 0.79934

Public 7 Non-Hispanic Black Male 303,320 407,354 264 0.74461

Public 7 Hispanic Male 449,797 477,449 288 0.94208

Public 7 Non-Hispanic Native American Male 23,776 85,157 46 0.27920

Public 7 Non-Hispanic White Male 1,024,017 995,070 595 1.02909

Public 8 Non-Hispanic Asian and 

Pacific Islander

Female 85,580 75,987 64 1.12625

Public 8 Non-Hispanic Black Female 288,628 351,500 262 0.82113

Public 8 Hispanic Female 422,768 525,017 334 0.80525

Public 8 Non-Hispanic Native American Female 22,312 53,138 36 0.41990

Public 8 Non-Hispanic White Female 968,394 950,659 604 1.01866

Public 8 Non-Hispanic Asian and 

Pacific Islander

Male 89,334 160,988 87 0.55491

Public 8 Non-Hispanic Black Male 295,815 316,285 246 0.93528

Public 8 Hispanic Male 437,034 488,241 300 0.89512

Public 8 Non-Hispanic Native American Male 22,800 60,940 40 0.37413

Public 8 Non-Hispanic White Male 1,022,119 1,004,476 635 1.01756

Public 9 Non-Hispanic Asian and 

Pacific Islander

Female 87,415 75,991 39 1.15034

Public 9 Non-Hispanic Black Female 321,224 348,610 225 0.92144

Public 9 Hispanic Female 441,642 671,598 327 0.65760

Public 9 Non-Hispanic Native American Female 23,819 41,497 27 0.57399

Public 9 Non-Hispanic White Female 1,015,797 1,177,688 576 0.86253

Public 9 Non-Hispanic Asian and 

Pacific Islander

Male 91,952 108,901 51 0.84436

Public 9 Non-Hispanic Black Male 344,666 375,947 245 0.91679
31

School 

Type Grade Race/Hispanic Origin Gender

(E) 

Control 

Total

(F) Weighted 

Estimate

No. of 

Cases

(G) PostStratification 

Adjustment

Public 9 Hispanic Male 472,389 679,719 320 0.69498

Public 9 Non-Hispanic Native American Male 25,536 94,239 45 0.27097

Public 9 Non-Hispanic White Male 1,082,621 966,286 479 1.12039

Public 10 Non-Hispanic Asian and 

Pacific Islander

Female 87,245 111,562 73 0.78203

Public 10 Non-Hispanic Black Female 298,317 313,559 240 0.95139

Public 10 Hispanic Female 399,950 605,250 323 0.66080

Public 10 Non-Hispanic Native American Female 22,167 63,699 34 0.34800

Public 10 Non-Hispanic White Female 996,755 1,008,757 536 0.98810

Public 10 Non-Hispanic Asian and 

Pacific Islander

Male 91,740 80,617 48 1.13796

Public 10 Non-Hispanic Black Male 302,961 325,913 218 0.92958

Public 10 Hispanic Male 414,302 512,161 265 0.80893

Public 10 Non-Hispanic Native American Male 23,140 60,152 39 0.38468

Public 10 Non-Hispanic White Male 1,042,853 1,013,084 530 1.02938

Public 11 Non-Hispanic Asian and 

Pacific Islander

Female 83,060 99,555 71 0.83432

Public 11 Non-Hispanic Black Female 270,278 351,841 253 0.76818

Public 11 Hispanic Female 351,600 544,487 271 0.64575

Public 11 Non-Hispanic Native American Female 20,462 20,532 17 0.99658

Public 11 Non-Hispanic White Female 955,058 958,612 509 0.99629

Public 11 Non-Hispanic Asian and 

Pacific Islander

Male 87,816 100,906 53 0.87028

Public 11 Non-Hispanic Black Male 260,589 304,663 222 0.85533

Public 11 Hispanic Male 354,460 598,732 300 0.59202

Public 11 Non-Hispanic Native American Male 20,769 37,656 21 0.55155

Public 11 Non-Hispanic White Male 988,539 923,544 473 1.07038

Public 12 Non-Hispanic Asian and 

Pacific Islander

Female 80,949 86,000 57 0.94126

Public 12 Non-Hispanic Black Female 259,801 290,926 214 0.89301

Public 12 Hispanic Female 324,717 458,577 231 0.70810

Public 12 Non-Hispanic Native American Female 19,339 21,221 17 0.91132

Public 12 Non-Hispanic White Female 941,752 1,039,769 592 0.90573

Public 12 Non-Hispanic Asian and 

Pacific Islander

Male 84,706 109,029 59 0.77691

Public 12 Non-Hispanic Black Male 240,128 274,341 198 0.87529

Public 12 Hispanic Male 318,489 503,767 305 0.63221

Public 12 Non-Hispanic Native American Male 19,505 45,957 27 0.42442

Public 12 Non-Hispanic White Male 969,959 937,071 530 1.03510

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 non-response at the school level. In particular, non-participating schools may 

lead to PSUs without student data for a given school level. All strata/level combinations but three had at least two 

PSUs. Stratum BR3 was combined with BR4 at both the high school and middle school levels, and stratum HR3 

was combined with stratum HR4 at the middle school level. 
32

Exhibit 4-5 displays the correspondence between the sampling strata and the analysis strata, which are represented

by two variables on the analysis file. Thus, the analytic file contains 14 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.

Exhibit 4-5: Sampling and Analysis Stratum Coding Schemes

High 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 113 HU3 213

BU4 114 HU4 214

Exhibit 4-6 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 (4-7a) and middle

schools (4-7b).

Exhibit 4-6a: Current Use Estimates for Selected Tobacco Products for High School Students

Current Use

Product Overall Female Male Non-Hispanic White Non-Hispanic Black Hispanic

Cigarettes 12.7% (.7) 11.2% (.8) 14.1% (1.0) 14.0% (1.0) 9.0% (1.1) 13.4% (1.3)

Cigar 11.9% (.6) 8.3% (.7) 15.4% (.8) 11.4% (.7) 14.7% (1.3) 12.1% (1.0)

Smokeless 

Tobacco

5.7% (.7) 1.7% (.3) 9.6% (1.1) 7.5% (1.0) 2.4% (.6) 4.0% (.5)

Hookah 5.2% (.4) 4.8% (.4) 5.6% (.5) 5.3% (.4) 2.4% (.5) 7.1% (.7)

Electronic 

Cigarettes

4.5% (.4) 3.5% (.4) 5.5% (.6) 4.8% (.6) 2.7% (.5) 5.3% (.6)
33

Exhibit 4-6b: Current Use Estimates for Selected Tobacco Products for Middle School Students

Current Use

Product Overall Female Male Non-Hispanic White Non-Hispanic Black Hispanic

Cigarettes 2.9% (.3) 2.8% (.4) 3.0% (.4) 2.6% (.4) 1.7% (.4) 5.1% (.7)

Cigar 3.1% (.4) 2.9% (.5) 3.3% (.4) 2.2% (.5) 4.5% (.9) 4.7% (.6)

Smokeless 

Tobacco

1.4% (.3) .8% (.2) 1.9% (.4) 1.4% (.4) .8% (.3) 1.8% (.4)

Hookah 1.1% (.2) 1.3% (.3) .9% (.2) .7% (.2) .9% (.3) 2.4% (.5)

Electronic 

Cigarettes

1.1% (.2) .9% (.2) 1.4% (.2) .9% (.2) 1.4% (.4) 1.8% (.4)

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:

Proc Surveymeans Data=nyts2013 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 2013, Estimates by School Type, by School Type and Sex Cross-Classified, and by School Type 

and Race/Ethnicity Cross-Classified”;

run;

SAS:

Proc Descript Data=nyts2013 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 2013, Estimates by School Type, by School Type and Gender Cross-Classified, and by School 

Type and Race Cross-Classified”;

Print Percent Sepercent / Style=NCHS;

run;
34

Appendix A: Questionnaire

Appendix A

Questionnaire
35

Form Approved

OMB No.: 0920-0621 

Expiration Date: 01/31/2015

National Youth

Tobacco Survey (NYTS)

2013 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).
36

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, Latina,, 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

This section ask about if you’ll try tobacco that is smoked or put in your mouth

6. At any time during the next 12 months do you think you will use any form of tobacco?

A. Definitely yes 

B. Probably yes 

C. Probably not 

D. Definitely not 
37

7. Do you think that you will try any form of tobacco soon?

A. Definitely yes 

B. Probably yes 

C. Probably not 

D. Definitely not

8. If one of your best friends were to offer you any form of tobacco, would you use it?

A. Definitely yes 

B. Probably yes 

C. Probably not 

D. Definitely not

The next five sections ask about your use of different kinds of tobacco products

The next 14 questions are about cigarettes.

9. Have you ever tried cigarette smoking, even one or two puffs? 

A. Yes 

B. No 

10. Do you think you will smoke a cigarette in the next year?

A. Definitely yes 

B. Probably yes 

C. Probably not 

D. Definitely not 

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

A. Definitely yes 

B. Probably yes 

C. Probably not 

D. Definitely not

12. 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

13. 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
38

14. 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)

15. 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

16. 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

17. 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

18. 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
39

19. 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

20. During the past 30 days, how did you get your own cigarettes? (You can CHOOSE ONE ANSWER or MORE THAN 

ONE ANSWER)

A. I did not get cigarettes during the past 30 days

B. I bought a pack of cigarettes myself

C. I had someone else buy a pack of cigarettes for me

D. I asked someone to give me a cigarette

E. Someone offered me a cigarette

F. I bought cigarettes from another person

G. I took cigarettes from a store or another person

H. I got cigarettes some other way 

21. During the past 30 days, where did you buy your own cigarettes? (You can CHOOSE ONE ANSWER or MORE THAN 

ONE ANSWER)

A. I did not buy cigarettes 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 

22. During the past 30 days, did anyone refuse to sell you cigarettes because of your age? 

A. I did not try to buy cigarettes during the past 30 days

B. Yes

C. No

The next five questions are about smoking cigars.

23. Have you ever tried smoking cigars, cigarillos, or little cigars, such as Black and Milds, Swisher Sweets, Dutch Masters, 

White Owl, or Phillies Blunts, even one or two puffs? 

A. Yes 

B. No 

24. 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
40

25. 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 

26. During the past 30 days, how did you get your own cigars, cigarillos, or little cigars? (You can CHOOSE ONE 

ANSWER or MORE THAN ONE ANSWER)

A. I did not get cigars, cigarillos, or little cigars 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 one

E. Someone offered it 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 

27. During the past 30 days, where did you buy your own cigars, cigarillos, or little cigars? (You can CHOOSE ONE 

ANSWER or MORE THAN ONE ANSWER) 

A. I did not buy cigars, cigarillos, or little cigars 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 

The next five questions are about using smokeless tobacco. Please do not think about using snus when you answer 

these questions.

28. 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 

29. How old were you when you used chewing tobaccos, 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
41

30. 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 

31. During the past 30 days, how did you get your own chewing tobacco, snuff, or dip? (You can CHOOSE ONE 

ANSWER or MORE THAN ONE ANSWER) 

A. I did not get chewing tobacco, snuff, or dip during the past 30 days

B. I bought it myself

C. I had someone else buy it for me

D. I asked someone to give me some

E. Someone offered it to me

F. I bought it from another person

G. I took it from a store or another person

H. I got it some other way 

32. During the past 30 days, where did you buy your own chewing tobacco, snuff, or dip? (You can CHOOSE ONE 

ANSWER or MORE THAN ONE ANSWER) 

A. I did not buy chewing tobacco, snuff, or dip 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 

 

The next two questions are about smoking tobacco in a pipe. Please do not think about smoking tobacco in a waterpipe or 

hookah when you answer these questions 

33. Have you ever tried smoking tobacco in a pipe, even one or two puffs? 

A. Yes 

B. No 

34. During the past 30 days, on how many days did you smoke tobacco in a pipe?

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
42

The next three questions are about other forms of tobacco.

35. Which of the following tobacco products have you ever heard of? (You can CHOOSE ONE ANSWER or MORE THAN 

ONE ANSWER) 

A. Roll-your-own cigarettes

B. Flavored cigarettes, such as Camel Crush

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

D. Clove cigars (kreteks) 

E. Flavored little cigars (such as mint, clove, spice, alcohol (wine, cognac), candy, fruit, chocolate, or other 

sweets)

F. Smoking tobacco from a hookah or a waterpipe

G. Snus, such as Camel or Marlboro Snus 

H. Dissolvable tobacco products, such as Ariva, Stonewall, Camel orbs, Camel sticks, or Camel strips 

I. Electronic Cigarettes or E-cigarettes, such as Ruyan or NJOY

J. Some other new tobacco products not listed here

K. I have never heard of any of the products listed above or any new tobacco product 

36. Which of the following tobacco products have you ever tried, even just one time? (You can CHOOSE ONE ANSWER 

or MORE THAN ONE ANSWER) 

A. Roll-your-own cigarettes

B. Flavored cigarettes, such as Camel Crush

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

D. Clove cigars (kreteks) 

E. Flavored little cigars (such as mint, clove, spice, alcohol (wine, cognac), candy, fruit, chocolate, or other 

sweets)

F. Smoking tobacco from a hookah or a waterpipe

G. Snus, such as Camel or Marlboro Snus 

H. Dissolvable tobacco products, such as Ariva, Stonewall, Camel orbs, Camel sticks, or Camel strips 

I. Electronic Cigarettes or E-cigarettes, such as Ruyan or NJOY

J. Some other new tobacco products not listed here

K. I have never tried any of the products listed above or any new tobacco product

37. In the past 30 days, which of the following products have you used on at least one day? (You can CHOOSE ONE 

ANSWER or MORE THAN ONE ANSWER) 

A. Roll-your-own cigarettes

B. Flavored cigarettes, such as Camel Crush

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

D. Clove cigars (kreteks) 

E. Flavored little cigars (such as mint, clove, spice, alcohol (wine, cognac), candy, fruit, chocolate, or other 

sweets)

F. Smoking tobacco from a hookah or a waterpipe

G. Snus, such as Camel or Marlboro Snus 

H. Dissolvable tobacco products, such as Ariva, Stonewall, Camel orbs, Camel sticks, or Camel strips 

I. Electronic Cigarettes or E-cigarettes, such as Ruyan or NJOY

J. Some other new tobacco products not listed here

K. I have not used any of the products listed above or any new tobacco product in the past 30 days

The next eleven questions ask about different issues related to tobacco.

38. How easy would it be for you to get tobacco products if you wanted some?

A. Very easy

B. Somewhat easy

C. Not easy at all

39. Do you believe that tobacco companies try to get young people under 18 to use tobacco products?

A. Yes

B. No
43

40. 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

41. When you read newspapers or magazines, how often do you see ads or promotions for cigarettes or other tobacco 

products?

A. I do not read newspapers or magazines

B. Never 

C. Rarely

D. Sometimes

E. Most of the time

F. Always

42. During the past 30 days, did you receive coupons from a tobacco company through... (You can CHOOSE ONE 

ANSWER or MORE THAN ONE ANSWER)

A. The mail

B. E-mail 

C. The Internet

D. Social Networks (such as Facebook and Twitter)

E. A text message

F. On a cigarette pack or other tobacco product

G. I did not receive coupons from a tobacco company

43. 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

44. During the past 30 days, how often did you see any ads or promotions for cigarettes or other tobacco products that were 

outdoors on a billboard or could be seen from outside a store? 

A. I did not see an ad for cigarettes or other tobacco products during the past 30 days

B. Never 

C. Rarely

D. Sometimes

E. Most of the time

F. Always

45. 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
44

46. What is the name of your favorite cigarette brand? (You can CHOOSE ONE ANSWER or MORE THAN ONE 

ANSWER)

A. American Spirit

B. Camel

C. GPC, Basic, or Doral

D. Kool 

E. Marlboro

F. Newport

G. Some other brand not listed here

H. I don’t have a favorite cigarette brand

I. Not sure

47. Have you seen or heard advertisements against tobacco with any of the following? (You can CHOOSE ONE ANSWER 

or MORE THAN ONE ANSWER)

A. A man who lost his legs from amputations (removal of body parts)

B. A woman who lost her fingers and toes from amputations (removal of body parts)

C. A man with a scar on his chest from a heart attack

D. A woman putting on a wig and putting in her teeth while getting dressed

E. A son bathing and caring for his mother on her bed because she had a stroke

F. A mom giving her son an inhaler because he has breathing problems from being around adults who smoke 

cigarettes

G. A man in the shower covering the hole in his neck

H. A child scratching because of chicken pox

I. Don’t know/Not sure

J. I haven’t seen or heard any of these advertisements

48. How soon after you wake up do you want to use a tobacco product?

A. I do not 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

Some cigarette or other tobacco companies make items like sports gear, T-shirts, hats, jackets,sunglassess or other 

items that people can buy or receive for free.

49. During the past 12 months, did you buy or receive anything such as a t-shirt, hat, sunglasses, that has a tobacco brand 

name, logo, or picture on it? 

A. Yes 

B. No 

50. 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

The next two questions are about visits to a doctor, dentist, nurse, or other health professional.

51. Think about each time that you visited a doctor, dentist, or nurse in the past 12 months. During any of these visits were 

you asked if you used tobacco that is smoked or put in your mouth?

A. I did not see a doctor, dentist, or nurse during the past 12 months

B. Yes

C. No
45

52. During the past 12 months, did any doctor, dentist, or nurse give you advice not to use tobacco that is smoked or put in 

your mouth?

A. I did not see a doctor, dentist, or nurse during the past 12 months

B. Yes

C. No

The next six questions are about quitting tobacco products.

53. 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 

54. 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

55. When you last tried to quit for good, how long did you stay off cigarettes? (PLEASE CHOOSE THE FIRST ANSWER 

THAT FITS)

A. I have never smoked cigarettes

B. I have never tried to quit

C. Less than a day

D. 1 to 7 days 

E. More than 7 days but less than 30 days

F. More than 30 days but less than 6 months

G. More than 6 months but less than 1 year

H. 1 year or more

56. 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 year

E. Yes, but not within the year

F. No, I am not thinking about quitting the use of all tobacco products

57. 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
46

58. In the past 12 months, did you do any of the following to help you quit using tobacco of any kind for good? (You can 

CHOOSE ONE ANSWER or MORE THAN ONE ANSWER)

A. I did not use tobacco of any kind during the past 12 months

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

C. Attended a program in my school 

D. Attended a program in the community 

E. Called a telephone help line or telephone quit line 

F. Used nicotine gum 

G. Used nicotine patch 

H. Used any medicine to help quit 

I. Visited an Internet quit site 

J. Got help from family or friends 

K. Used another method, such as hypnosis or acupuncture

L. Tried to quit on my own or quit “cold turkey”

The next five questions ask about you being around other people’s tobacco smoke.

59. During the past 7 days, on how many days did someone smoke tobacco products in your home while you were there?

A. 0 days

B. 1 day

C. 2 days

D. 3 days

E. 4 days

F. 5 days

G. 6 days

H. 7 days

60. During the past 7 days, on how many days did you ride in a vehicle were someone was smoking a tobacco product?

A. 0 days

B. 1 day

C. 2 days

D. 3 days

E. 4 days

F. 5 days

G. 6 days

H. 7 days

61. During the past 7 days, on how many days did you breathe the smoke from someone who was smoking a tobacco

product at your school, including school buildings, school grounds, and school parking lots?

A. 0 days

B. 1 day

C. 2 days

D. 3 days

E. 4 days

F. 5 days

G. 6 days

H. 7 days

62. During the past 7 days, on how many days did you breathe the smoke from someone who was smoking tobacco 

products in the place where you work?

A. I do not have a job

B. I did not work during the past 7 days

C. 0 days

D. 1 day

E. 2 days

F. 3 days

G. 4 days

H. 5 days

I. 6 days

J. 7 days
47

63. During the past 7 days, on how many days did you breathe the smoke from someone who was smoking tobacco 

products in an indoor or outdoor public place? Examples of indoor public places are school buildings, stores, 

restaurants, and sports arenas. Examples of outdoor public places are school grounds, parking lots, stadiums and 

parks.

A. 0 days

B. 1 day

C. 2 days

D. 3 days

E. 4 days

F. 5 days

G. 6 days

H. 7 days

The next five questions ask about smoking and other tobacco use in your home, your family's cars, and by your friends 

and family.

64. Inside your home (not counting decks, garages, or porches) is smoking...

A. Always allowed

B. Allowed only at some times or in some places

C. Never allowed

65. In the vehicles that you and family members who live with you own or lease, is smoking... 

A. Always allowed 

B. Sometimes allowed 

C. Never allowed

66. Does anyone who lives with you now...? (CHECK ALL THAT APPLY).

A. Smoke cigarettes

B. Use chewing tobacco, snuff, or dip

C. Use snus

D. Smoke cigars, cigarillos, or little cigars

E. Smoke tobacco using a hookah or waterpipe

F. Smoke tobacco out of a pipe other than a hookah or waterpipe

G. Smoke bidis (small brown cigarettes wrapped in a leaf)

H. Smoke clove cigarettes (kreteks)

I. Use any other form of tobacco

J. No one who lives with me now uses any form of tobacco

67. How many of your closest friends use any form of tobacco? 

A. None 

B. One 

C. Two 

D. Three 

E. Four 

F. Five or more

G. Not sure 

68. Out of every 10 students in your grade at school, how many do you think smoke cigarettes?

A. 0

B. 1

C. 2

D. 3

E. 4

F. 5

G. 6

H. 7

I. 8

J. 9

K. 10
48

The next seven questions are about your thoughts about tobacco.

69. In your opinion, inside your home, smoking tobacco products should.... 

A. Always be allowed

B. Be allowed only at some times or in some places

C. Never be allowed

70. In your opinion, in their vehicles, people should ...

A. Always allow smoking

B. Sometimes allow smoking

C. Never allow smoking

71. 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

72. Do you believe any of the following are less harmful than smoking cigarettes? (You can CHOOSE ONE ANSWER or 

MORE THAN ONE ANSWER) 

A. Smoking tobacco from a hookah or waterpipe

B. Smoking tobacco from a pipe other than a waterpipe

C. Smoking Bidis (small brown cigarettes wrapped in a leaf)

D. Smoking Clove cigarettes (kreteks)

E. Smoking flavored cigars, little cigars, and cigarillos (such as mint, clove, spice, alcohol (wine, cognac), candy, 

fruit, chocolate, or other sweets)

F. Smoking cigars, cigarillos, or little cigars (those that are not flavored)

G. Using electronic cigarettes, such as Ruyan or NJOY

H. Do not know

I. I do not believe that any of the above products are less harmful than cigarettes.

73. Do you believe any of the following are less harmful than smoking cigarettes? (You can CHOOSE ONE ANSWER or 

MORE THAN ONE ANSWER)

A. Using chewing tobacco, snuff, or dip

B. Using snus, such as Camel or Marlboro Snus

C. Using dissolvable tobacco products, such as Ariva, Stonewall, Camel orbs, Camel sticks, Marlboro sticks, or 

Camel strips 

D. Using electronic cigarettes, such as Ruyan or NJOY

E. Do not know

F. I do not believe that any of the above products are less harmful than 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
49

The last six questions are about your experiences at home, in your community, and at school.

76. Would your parents or guardians strongly disapprove if you used tobacco products?

A. I don’t use tobacco products, and my parents would strongly disapprove if I did

B. I don’t use tobacco products, and my parents would not strongly disapprove if I did

C. I use tobacco products, and my parents strongly disapproved when they first found out

D. I use tobacco products, and my parents did not strongly disapprove when they first found out

E. I use tobacco products, but my parents don’t know, and they would strongly disapprove if they knew

F. I use tobacco products, but my parents don’t know, and they would not strongly disapprove if they knew 

77. During the past 12 months, have you been involved in any organized activities to keep people your age from using any 

form of tobacco product?

A. Yes 

B. No 

78. During this school year, were you taught in any of your classes about why you should not use tobacco products?

A. Yes

B. No

79. During the past 30 days, to your knowledge, has anyone, including yourself, smoked a tobacco product on school 

property when he or she was not supposed to?

A. Yes

B. No

80. During the past 30 days, to your knowledge, has anyone, including yourself, used some other type of tobacco product 

(that is, one that is not smoked) on school property when he or she was not supposed to?

A. Yes

B. No

81. During the past 30 days, how many days did you miss at least one class period because you skipped or "cut" or just 

did not want to be there?

A. 0 days 

B. 1 day 

C. 2 to 5 days 

D. 6 to 10 days 

E. 11 or more days 
50

B:

2012 National Youth Tobacco Survey (NYTS) Data Collector Training Agenda
51
52

Appendix D: School Sampling Weights

Appendix B

Student Weight Detail
53

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 – as are the other stage sampling weights – followed 

by two adjustments, one for non-response, and another post-stratifying 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 

Non-Response Adjustment

The non-response 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 non-response 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
54

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



 

 

  
55

Appendix F: Common Core of Data Race/Ethnicity Definitions

Appendix C Common Core of Data

Race/Ethnicity Definitions
56

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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