Appendix F_2020 NSCH Methodology Report

Appendix F

2020 National Survey of Children’s Health
Methodology Report

September 30th, 2021 

  2020 National Survey of Children’s Health 
Methodology Report

The U.S. Census Bureau reviewed this data product for unauthorized disclosure of confidential information 
and approved the disclosure avoidance practices applied to this release. CBDRB-FY21-POP001-0198

Contents

Abstract ......................................................................................................................................................... 5
Objectives.................................................................................................................................................. 5
Methods .................................................................................................................................................... 5
Results ....................................................................................................................................................... 5
Introduction .................................................................................................................................................. 6
Survey History ............................................................................................................................................... 7
Frame, Sample, and Selected Child Subsample ............................................................................................ 8
Frame and Sample Selection ..................................................................................................................... 8
Selected Child Subsample ......................................................................................................................... 9
Data Collection ............................................................................................................................................ 11
Survey Content ........................................................................................................................................ 11
2020 Content Changes ............................................................................................................................ 12
Data Collection Instruments ................................................................................................................... 13
Treatment Groups ................................................................................................................................... 17
Mailing Contents and Schedule .............................................................................................................. 18
Response Analysis ....................................................................................................................................... 22
Response Rates ....................................................................................................................................... 22
Item-Level Response ............................................................................................................................... 24
Treatment Groups and Response ........................................................................................................... 26
Data Processing ........................................................................................................................................... 31
Unduplication .......................................................................................................................................... 31
Paper to Web Standardization ................................................................................................................ 32
Data Edits ................................................................................................................................................ 32
Recoded and Standardized Variables ..................................................................................................... 34
Missing Values and Imputation............................................................................................................... 38
Suppressed Variables .............................................................................................................................. 40
Geography Variables ............................................................................................................................... 41
Weighting Specifications ............................................................................................................................. 43
Overview ................................................................................................................................................. 43
Population Controls ................................................................................................................................ 46
Limitations............................................................................................................................................... 47
Estimation, Hypothesis Testing, and Data Use Guidelines ......................................................................... 48
Variance Estimation ................................................................................................................................ 48
Combining Data across Survey Years ...................................................................................................... 49
Confidentiality ......................................................................................................................................... 49
Guidelines for Data Use .......................................................................................................................... 49
Supporting Material .................................................................................................................................... 51
References .............................................................................................................................................. 51
Attachment A: 2020 Estimated State-Level Sample Sizes .......................................................................... 52

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Attachment B: Probabilities for Selected Child........................................................................................... 54
Attachment C: Envelope Design Options .................................................................................................... 56
Attachment D: Weighted Response Rates by State .................................................................................... 61

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Table of Figures
Table 1. Web Submission Times (in Minutes).............................................................................................. 14
Table 2. TQA Purpose Codes used in ATAC System ..................................................................................... 16
Table 3. Production Mailout Schedule ........................................................................................................ 19
Table 4. Topical Mailings and Topical Mailing Groups ............................................................................... 21
Table 5. 2020 Final Dispositions (Unweighted) ........................................................................................... 22
Table 6. 2020 NSCH Weighted Response Rates .......................................................................................... 24
Table 7. Lowest Item-Level Response Rates ................................................................................................ 25
Table 8. Data Collection Costs and Completed Questionnaires by Screener Incentive ............................... 27
Table 9. Data Collections Costs and Returns by Topical Incentive .............................................................. 27
Table 10. Response Odds Ratios (Incentive versus No Incentive) by Education, Race, and Income ........... 28
Table 11. Unduplication Criteria for both Web and Paper Returns ............................................................ 31
Table 12. Unduplication Criteria for Two Paper Returns ............................................................................ 32
Table 13. Standardized Variables................................................................................................................ 34
Table 14. Derived and Recoded Variables ................................................................................................... 34
Table 15. Imputed Variables and Their Imputation Flags ........................................................................... 39
Table 16. Suppressed Variables .................................................................................................................. 40
Table 17. List of Geography Variables ........................................................................................................ 41
Table 18. Geographies Identified at the Intersections ................................................................................ 42
Table 19. Collapsed Dimensions of Final Raking and Affected States......................................................... 47
Table A-1: Address Sample Size and Strata Distribution by State19 ........................................................... 52
Table B-1: Household Type Assignment from the Values of Five Screener Variables19 ............................. 54
Table D-1. Weighted Response Rates by State19 ....................................................................................... 61

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Abstract
Objectives

This report details the development, plan, and operation of the 2020 National Survey of Children’s
Health (NSCH). This survey is designed to provide national and state-level estimates on key indicators of
the health and well-being of children, their families and communities, as well as information about the
prevalence and impact of special health care needs. Funding and direction for this survey was provided
by the Health Resources and Services Administration’s Maternal and Child Health Bureau (HRSA MCHB)
within the U.S. Department of Health and Human Services. The U.S. Census Bureau conducted the
survey on behalf of HRSA MCHB.

Methods

The 2020 NSCH used a national sample of 240,000 addresses. During data collection, a screener
questionnaire was used to identify households with children and roster children in the household. The
screener questionnaire also included a battery of questions to identify children with special health care
needs. One child was randomly selected from each eligible household, and that child was the subject of
a more detailed topical questionnaire. Responses to the screener and topical questionnaires were
collected, processed, and published in the Screener Public Use File and Topical Public Use File.

Results

The weighted Overall Response Rate for the 2020 NSCH was 42.4%. A total of 93,500 1 screener
questionnaires were completed, and of those 51,107 were eligible for topical questionnaire follow-up.
Of those topical-eligible households, 42,777 completed a topical interview. Weighted estimates from
the Topical file generalize to state and national resident child populations. Weighted estimates from the
Screener file generalize to state and national resident child populations (using the child weight) and
households with children by state and nationally (using the household weight).

1

Rounded to the nearest five hundred in accordance with the U.S. Census Bureau disclosure avoidance practices.
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Introduction
The 2020 National Survey of Children’s Health (NSCH) was conducted by the U.S. Census Bureau for the
Health Resources and Services Administration, Maternal and Child Health Bureau (HRSA MCHB) within
the U.S. Department of Health and Human Services (HHS). As stated in the Office of Management and
Budget Clearance Package, the purpose of the NSCH is to “collect information on factors related to the
well-being of children, including access to and quality of health care, family interactions, parental health,
school and after-school experiences, and neighborhood characteristics.” 2 This document details the
objectives, methodologies, and results of the 2020 NSCH into seven sections.
•

Survey History. The 2020 NSCH was the fifth annual production following the redesign and
merging of the previous NSCH and National Survey of Children with Special Health Care Needs
(NS-CSHCN).

•

Frame, Sample and Selected Child Subsample. A screener questionnaire identified households
with children and rostered the children in those households. A topical questionnaire collected
detailed information about one child selected at random from the household.

•

Data Collection. Data were collected using a two-stage paper survey instrument and a singlestage web-based survey instrument. This section discusses treatment groups, mail schedule and
data capture methods for the web, paper, and telephone questionnaire assistance operations.

•

Response Analysis. This section discusses the calculation of response rates along with analyses
of survey breakoffs, item nonresponse, and treatment group comparisons.

•

Data Processing. Web and paper survey responses were cleaned for analysis, including
unduplication of responses, edits for data quality, creating standardized and derived variables,
and imputation of missing values.

•

Weighting Specifications. Weights allow for estimates to be generalized to state and national
child resident populations (Screener and Topical file) and households with children (Screener
file).

•

Estimation, Hypothesis Testing, and Data Use Guidelines. A discussion of the best practices for
data users and limitations of the 2020 NSCH.

The Office of Management and Budget Clearance Package is available at
https://www.reginfo.gov/public/do/PRAViewDocument?ref_nbr=202003-0607-001

2

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Survey History
The Health Resources and Services Administration’s Maternal and Child Health Bureau (HRSA MCHB),
within the U.S. Department of Health and Human Services (HHS), has sponsored the National Survey of
Children’s Health (NSCH) 3 and its companion survey, the National Survey of Children with Special Health
Care Needs (NS-CSHCN), 4 since 2001. HRSA MCHB has provided funding and direction for the two
periodic surveys to provide both national and state estimates of key indicators of child health and wellbeing for children ages 0-17 years.
Together, these surveys provided critical data on key measures of child health; the presence and impact
of special health care needs; health care access, utilization, and quality; and the family and community
factors that impact child and adolescent health and well-being. Both surveys were fielded three times
(NS-CSHCN 2001, 2005-06, and 2009-10; NSCH 2003, 2007, and 2011-12) as modules of the State and
Local Area Integrated Telephone Survey (SLAITS) system by the Centers for Disease Control and
Prevention’s National Center for Health Statistics. As part of the SLAITS system, the surveys utilized a
random-digit-dial sample of landline telephone numbers, with cell-phone supplementation in the last
year of administration for both surveys.
In 2015, HRSA MCHB redesigned the NSCH and the NS-CSHCN into a single combined survey that utilized
an address-based sampling frame. When this newly consolidated survey was first fielded in 2016 it
incorporated questions from the former surveys and retained the NSCH name. The U.S. Census Bureau
now conducts the NSCH annually on behalf of HRSA MCHB and HHS under Title 13, United States Code,
Section 8(b), which allows the Census Bureau to conduct surveys on behalf of other agencies.

Blumberg SJ, Foster EB, Frasier AM, et al. 2012. Design and Operation of the National Survey of Children’s Health,
2007. National Center for Health Statistics. Vital Health Stat, 1(55).
http://www.cdc.gov/nchs/data/series/sr_01/sr01_055.pdf
4
Bramlett MD, Blumberg SJ, Ormson AE, et al. 2014. Design and Operation of the National Survey of Children with
Special Health Care Needs, 2009–2010. National Center for Health Statistics. Vital Health Stat, 1(57).
http://www.cdc.gov/nchs/data/series/sr_01/sr01_057.pdf
3

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Frame, Sample, and Selected Child Subsample
The 2020 NSCH sampled approximately 240,000 addresses to participate in the survey. One child from
each household with children was selected, or subsampled, to be the subject of the topical
questionnaire. This section covers the design of the sample and subsample.

Frame and Sample Selection

The 2020 NSCH used an address-based sample selected from an extract of the Census Bureau’s Master
Address File (MAF) 5. It covers the 50 states and the District of Columbia 6. The sample frame uses
administrative records-based flags to identify three mutually exclusive strata:
•
•

•

Stratum 1: Addresses that are explicitly linked to children using administrative records.
Approximately 80% of these addresses are households with children.
Stratum 2a: Addresses that are probabilistically linked to children using administrative records
and block group characteristics. Approximately 15% of these addresses are households with
children.
Stratum 2b: The remaining addresses. Less than 5% of these addresses are households with
children.

Addresses assigned to Stratum 1 are explicitly linked to a child record either directly or through a parent
using administrative and survey records. Data sources include:
•
•
•
•
•
•
•
•

Social Security applications and the Census Numident
IRS 1040s and 1099s
Medicare Enrollment Database (MEDB)
Indian Health Service database (IHS)
Selective Service System (SSS)
Public Indian Housing Information Center (PIC) and Tenant Rental Assistance Certification
System (TRACS) data from the Department of Housing and Urban Development (HUD)
National Change of Address data from the US Postal Service
American Community Survey and CPS-ASEC, and the 2010 Census Unedited files (for parentchild links)

Approximately 38 million unique addresses were linked to at least one child record and assigned to
Stratum 1.
The remaining addresses were then subdivided into Strata 2a and 2b. All Stratum 2 addresses were
assigned a probability of child presence using administrative records and small-area geographic
characteristics. Beginning with those addresses with the lowest probability of children presence,
addresses were assigned to Stratum 2b by state until the stratum represented at most 5% of households
with children in that state (as reported in the 2018 American Community Survey). All other addresses
The MAF is a Title 13 data source, and all data collected are confidential under 13 U.S.C. Section 9. All access to
Title 13 data from this survey is restricted to Census Bureau employees and those holding Census Bureau Special
Sworn Status pursuant to 13 U.S.C. Section 23(c).
6
Hereafter, ‘state’ will include the District of Columbia.
5

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were assigned to Stratum 2a, and Strata 1 and 2a combined represented 95% of households with
children in each state.
To increase the efficiency of the sample, addresses in Stratum 1 were sampled at a higher rate than
addresses in Stratum 2a, and addresses in Stratum 2b were excluded from sampling. For the sample
selection:
•

•

•

•

The sampling rates by strata in each state were optimized to maximize the number of
households without children in each state without compromising the reliability of survey
estimates. Nationally, 61% of addresses came from Stratum 1 and 39% from Stratum 2a.
The addresses within each state were first sorted by strata, then organized into two groups by
the block group 7 poverty rate to ensure states had proportional representation of addresses in
high poverty areas selected for the sample.
The sample was distributed across states to produce a roughly equal number of completed
interviews per state. Four states included an oversample (see Attachment A) to increase the
number of interviews completed in those states.
To minimize respondent burden, addresses can be selected only once in any five-year period.

Selected Child Subsample
The screener questionnaire collects information on the presence of children within the household, child
demographic information, and basic questions about each child’s health. 8 One child is selected from the
completed screener, and one of three age-based topical questionnaires is provided to the household
based on the sampled child’s age:
•
•
•

NSCH-T1: children aged 0 through 5,
NSCH-T2: children aged 6 through 11, or
NSCH-T3: children aged 12 through 17

The probability of selection for a child is based on the number of children in the household, the special
health care needs status, and the age of the child. When appropriate, an 80% oversample is applied to
children with special health care needs and a 60% oversample to young children (ages 0-5). 9 See
Attachment B for more details. 10

A Census block group is a geographical unit with 600 to 3,000 population. Census blocks are grouped into block
groups; block groups, in turn, are grouped into Census tracts. The block group is the smallest scale geographical
unit for which the Census Bureau publishes sample statistics, i.e., estimates based on a sample of residents in the
block group. Consequently, it is the smallest scale geographical unit that could be used for this exercise.
8
Bethell CD, Read D, Neff J, Blumberg SJ, Stein RE, Sharp V, Newacheck PW. 2002. “Comparison of the Children
with Special Health Care Needs Screener to the Questionnaire for Identifying Children with Chronic Conditions—
Revised.” Ambulatory Pediatrics, Jan-Feb 2(1): 49-57.
9
The 80% oversample is applicable only for those households with both CSHCN and Non-CSHCN present. The 60%
age-based oversample is applicable when the conditions of the CSHCN oversample are not met and there are both
young (ages 0-5) and older (ages 6-17) children present.
10
Eligible children in a household are sorted first by special health care needs status (CSHCN then Non-CSHCN) and
7

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For mailed-in screener responses, the appropriate topical questionnaire is mailed to the household, and
mail materials indicate which child has been selected. In the web-based instrument, the child’s reported
age is used to navigate the respondent to age-appropriate survey items.

then by age (youngest to oldest). Additionally, children with the same special health care needs status and age are
sorted by name. In households with four or more eligible children, children are sorted first on special health care
needs status, then alphabetically by name, and then by age.
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Data Collection
Data collection efforts for the 2020 National Survey of Children’s Health (NSCH) began on July 27, 2020
and continued until January 22, 2021. The 2020 NSCH retained a two-phase data collection approach:
(1) an initial household screener to assess the presence, basic demographic characteristics, and special
health care needs status of any children in the home; and (2) a substantive topical questionnaire to be
completed by a parent or caregiver of the selected child. The data collection methodology employed
strategies to increase response, including clear and concise question wording, providing response mode
options, cash incentives and other treatments.
This section covers survey content and 2020 content changes, data collection instruments, and the data
collection process.

Survey Content
Questionnaires were designed to encourage cooperation by prospective respondents, enhance
respondent comprehension, and make instructions clear and simple. Questions were developed and
grouped by subject area to create logical, clear questionnaires with concrete question wording and
simple grammar.
The screener questionnaire consisted of two sections. The first section contained four questions about
the presence of children in the home, the primary language spoken, and home tenure (rent or own). The
next section contained detailed questions about the demographics and health of children in the
household.
There were three different topical questionnaires tailored to three child age groups: NSCH-T1 for 0 to 5year-old children, NSCH-T2 for 6 to 11-year-old children, and NSCH-T3 for 12 to 17-year-old children. All
three questionnaires contained 11 sections about the child, their family and neighborhood, but the
specific questions were tailored to be relevant to children in that age range. Copies of the screener and
topical questionnaires can be found at https://www.census.gov/programs-surveys/nsch/technicaldocumentation/questionnaires.html.
Section A. This Child’s Health
Current or lifelong physical, mental, behavioral, learning, or developmental conditions, and the impact
of these conditions on the child’s activities.
Section B: This Child as an Infant
Birth-related questions including birth weight, breastfeeding, and use of formula. Infant feeding
questions are only included on NSCH-T1.
Section C: Health Care Services
Health care providers and the child’s need for and use of medical, dental, mental, and specialized health
services in the last 12 months.

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Section D: Experience with This Child’s Health Care Providers
Frequency of care and satisfaction with the child’s health care providers, and how the child’s doctor or
health care providers worked with the child. NSCH-T3 includes questions about the child’s preparation
for transition into adult health care.
Section E: This Child’s Health Insurance Coverage
Status and adequacy of health insurance coverage, including any gaps in health insurance coverage in
the past 12 months.
Section F: Providing for this Child’s Health
Cost of health care in the past 12 months and time spent providing and arranging for the child’s health
care.
Section G: This Child’s Learning/Schooling and Activities
Early language development and learning for children ages 1 to 5 years. For children ages 6 to 17 years,
experiences at school, participation in organized activities, and physical activities.
Section H: About You and This Child
Daily life and household activities, including the child’s sleep habits, screen time, and the demands of
parenting/caregiving on the respondent.
Section I: About Your Family and Household
Frequency of family meals, the use of tobacco in the home, how the family copes with problems, food
adequacy, and adverse childhood experiences. Also, the respondent’s perception of their neighborhood
(e.g., amenities, safety).
Section J: About You and Other Parent or Caregiver in the Household
Demographic information of up to two adults in the household who are the child’s primary caregivers.
Section K: Household Information
Household count, family count, and family income.

2020 Content Changes

Seven variables were added to the 2020 NSCH questionnaires and reported on the public use
data files:
•
•
•
•
•
•
•

HEART_BORN (“Was this child born with the condition?”)
ACE12 (“To the best of your knowledge, has this child EVER experienced any of the following:
o Treated or judged unfairly because of their sexual orientation or gender identity?”)
A1_EMPLOYED (“Which of the following best describes your current employment status?”)
A2_EMPLOYED (“Which of the following best describes this caregiver's current employment
status?”)
CONCUSSION (“Do you think this child has ever had a concussion or brain injury?”)
SEEKCARE (“Did you seek medical care [for the concussion or brain injury] from a doctor or
other health care provider?”)
CONFIRMINJURY (“Did a doctor or other health care provider tell you that this child had a

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concussion or brain injury?”)
Responses to these items are reported on NSCH-T1, NSCH-T2, and NSCH-T3 and included in
the Topical Public Use File.
Additionally, the questions and response options were updated to reflect gender neutral pronouns.
Changes to question wording and response options since 2016 are noted in the NSCH codebook
(https://www.census.gov/data-tools/demo/uccb/nschdict).

Data Collection Instruments

The data collection design focuses on efforts to increase response rates. Respondents have multiple
options to respond to the survey and receive assistance including:
• Web Instrument (English and Spanish)
• Paper Instrument (English and Spanish)
• Telephone Questionnaire Assistance (TQA) (available in several languages)
• Email Questionnaire Assistance (EQA)
Web Instrument
The web survey was programmed using the U.S. Census Bureau’s Centurion system for internet data
collection. This software presented the questionnaire on a computer screen or other electronic device,
e.g., tablet or cellphone. The interview was self-administered by the respondent. The mailed invitation
included the survey URL and a unique 8-digit login ID.
Respondents were asked to verify their address. If the respondent answered that the address selected
for the sample (and displayed on screen) did not match their own, the survey was concluded and the
address was removed from further mailings.
If the listed address matched the respondent’s residence, the case was assigned a PIN that the
respondent would need to log back into the survey. Alternatively, the respondent could create a new
PIN by correctly answering a security question, which the respondent previously provided during the
original PIN creation process.
After setting up the PIN, the respondent reported the number of children (0-17 years of age) that usually
resided at that address. If there were no children that usually resided at the address, the survey was
concluded and the address removed from further mailings. If there were children that usually resided at
the address, the respondent was then directed through the rest of screener questionnaire.
There were two hard edits programmed into the web instrument which required the respondent to
provide a valid answer before continuing. These answers were necessary for subsampling: child’s first
name, initials, or nickname; and child’s age. Respondents were able to skip all other questions and
continue the survey.
After the respondent completed the screener questionnaire, the web instrument applied the
subsampling methodology to select one child from each household to be the subject of the topical
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questionnaire. At this point in the survey process, content from the screener portion of the
questionnaire was locked.
The name of the selected child was then prefilled into some topical questions, and the web instrument
guided respondents through skip patterns. Some response fields only accepted responses that
represented legitimate values; other fields offered a “pick list” of response categories. There were soft
edits for some questions that prompted respondents to provide an answer or revise an existing answer,
but respondents were able to continue past these edits without changing their answers.
Respondents could review and edit any answers before submitting. Once the survey was submitted, a
submission confirmation screen appeared with the date and time of completion. The instrument was
then locked and the respondent was only able to view the submission confirmation screen if they logged
back in. Submitted responses were saved in the output data file.
Respondents from households without children completed the web instrument in an average of 1
minute, 7 seconds. Respondents from households with children completed the screener portion of the
instrument in 5 minutes, 19 seconds; the web topical portion in 30 minutes, 13 seconds; and the entire
web instrument in 35 minutes, 32 seconds, on average. Online help screens and text were also available
in the instrument to aid respondents.
Table 1. Web Submission Times (in Minutes)
With Children
No Children
Mean
Median
Mean
Median
Screener
5.3
4.2
1.1
0.7
Topical
30.2
26.0
Total
35.5
30.8
1.1
0.7
Paper Instrument
The second mode of data collection was a two-phase, self-administered mail survey using paper
questionnaires. The paper questionnaires were created using Amgraf One Form Plus. They were printed,
trimmed, and stitched through an in-house print on-demand process using a Docuprint system that
allowed personalization to each respondent.
In the first phase of this mode of data collection, paper screener questionnaires were mailed to High
Paper addresses with the initial invitation, and to all other addresses (High Web) with the second nonresponse follow-up mailing. 11 Respondents completed a screener questionnaire to determine if there
were any children 17 years of age or younger who usually lived or stayed at the address. Resident
children were rostered in the screener instrument. Detailed information was collected for up to four
children, while basic information (name, age, sex) was collected for an additional six children.

More information on the High Web/High Paper group assignments is covered in the Mailout Content and
Schedule section.
11

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If the respondent mailed back the screener, it was then processed to determine if eligible children
usually resided at the address. Returned forms were processed by iCADE to capture responses through
OMR (optical mark recognition), OCR (optical character recognition), and KFI (keying from image). If the
respondent answered that the address selected for the sample did not match their own or that there
were no children that usually resided at the address, the survey was concluded and the household was
removed from further mailings. If the respondent listed children that usually resided at the address,
Census Bureau staff applied the subsampling methodology to select one child from the household roster
to be the subject of the topical questionnaire.
In the second phase, households that reported eligible children were mailed one of three age-based
topical questionnaires requesting more information about the selected child living at the address. To
ensure respondents answered the topical questions for the selected child, Docuprint systems printed
the selected child’s first name, initials, or nickname, age, and sex provided on the screener
questionnaire onto the invitation letter and paper questionnaire.
The paper and web instruments were designed to be as similar as possible to minimize the influence of
mode on responses. While automatic skips and soft edits could not be implemented in the paper
instrument, the questionnaire did include skip instructions within the question wording to mimic the
web instrument.
Telephone Questionnaire Assistance (TQA)
The National Processing Center call center in Tucson, Arizona provided telephone questionnaire
assistance (TQA) for the 2020 NSCH. Respondents could call a toll-free telephone line if they had
questions about the survey, wanted to complete the interview over the phone using the web
instrument, or submit feedback. All mail content and the web instrument listed this toll-free number.
Interviewers were trained to use the Automated Tracking and Control (ATAC) system to report call-ins
using one of the TQA purpose codes seen in Table 2.

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Table 2. TQA Purpose Codes used in ATAC System
TQA Purpose Codes

Definitions

03

Questionnaire completed - Children in the household

04

Questionnaire completed – No children in the household

02

Refusal to participate

07

Confirmed correct address

08

Confirmed incorrect address

09

Out-of-Scope (vacant, business, not a full-time residence)

10

Spanish questionnaire completed

12

Child moved and/or doesn’t live at residence most of the time

20

Questions about incentive

29

Paper questionnaire status

30

Request English paper questionnaire

31

Request Spanish paper questionnaire

32

Trouble completing paper questionnaire

33

Child listed on questionnaire is deceased

51

Centurion issues – PIN and/or LoginID issue

52

Centurion issues – Other

53

Centurion issues – RESET case

60

Questions about the survey (FAQs)

80

None of the above

If any changes were needed to the ATAC TQA instrument based on comments received from
interviewers, the survey team coordinated programming updates. All updates to procedures were
communicated to the TQA interviewers. Incoming call volumes were also monitored throughout data
collection and interviewer schedules were adjusted accordingly.
For the 2020 NSCH, approximately 3,600 TQA calls were recorded in ATAC. The most common outcomes
of these calls included ‘questionnaire completed – no children in the household’ (~1800), ‘confirmed
correct address’ (~700), and ‘questionnaire completed – children in the household’ (~300).
Email Questionnaire Assistance (EQA)
In addition to the toll-free telephone line, respondents were able to interact with Census Bureau staff
via email. An email address ([email protected]) was listed on all invitation letters and on the
Centurion login page. Emails were answered by call center staff in Tucson, Arizona. Staff checked the
email inbox daily and replied to respondents’ messages within 2 business days when possible. Emails
were logged in a tracking spreadsheet and cases were assigned purpose codes similar to the TQA
purpose codes in Table 2.

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EQA agents employed scripted responses for common concerns and questions. These scripts ensured
consistent and accurate information. When replying to the messages, agents removed any information
in the response email that could be considered personally identifiable (e.g., address, phone number,
name).
Spanish Language Translation
The NSCH paper and web instruments were available in both English and Spanish. The Census Bureau
reviewed and verified text from the 2019 Spanish-language questionnaires and provided new
translations where necessary for the 2020 questionnaires. Respondents could request a Spanishlanguage questionnaire by calling TQA. Spanish-speaking respondents that called the TQA line were
placed in a Spanish-language calling queue; a trained Spanish-language agent then answered any
questions or administered the Spanish-language web instrument over the phone. The agent flagged the
case if a Spanish paper questionnaire was requested and informed the respondent that a questionnaire
would arrive in the mail within three weeks.
If a respondent returned a Spanish-language paper screener questionnaire indicating the presence of
children in the household, the Spanish-language topical questionnaire was subsequently mailed to the
household. The web instrument included a toggle on every page that allowed respondents to switch
between the English and Spanish-language versions of the instrument.

Treatment Groups

Respondent contact strategies and letters were carefully designed to capture the attention of the
respondent and pique interest in the subject matter. To increase response and minimize nonresponse
bias, the survey sample was divided into treatment and control groups for various experiments. The
2020 NSCH treatments were:
•
•
•
•
•
•

Screener Cash Incentives
Topical Cash Incentives
Mixed Mode (High Paper) vs. Web-Push (High Web)
Mailing Package Redesign
Flat Mail Envelope
Priority Mail Envelope

Screener Cash Incentives
In the initial mailing for screener questionnaires, 90% of the sample received a small denomination bill
as an incentive to complete the survey, 30% receiving a $2 bill and 60% a $5 bill. The other 10% of the
sample did not receive an incentive and represented the control group for monitoring the effectiveness
of the incentive treatments.
Topical Cash Incentives
Among the households that were mailed a paper topical questionnaire, 90% received a $5 bill in the
initial topical mailing. The other 10% did not receive an incentive.

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Mixed Mode (High Paper) vs. Web-Push (High Web)
The High Paper treatment group was composed of the 30% of addresses identified as having the highest
probability of responding by paper only, and were contacted using a mixed-mode strategy. These
addresses received a paper screener questionnaire and an invitation to respond by web in the first
contact. The remaining 70% of addresses (High Web) were contacted using a web-push strategy. These
addresses were mailed only the invitation to respond by web in the first and second contact attempts.
More information about the mailout schedule is included in the Data Collection section.
Mailing Package Redesign
30% of the sample was randomly selected to receive redesigned mail materials throughout data
collection. The remaining 70% received the traditional NSCH envelope and accompanying materials.
More information about mailing contents is included in the Data Collection section. For a comparison of
materials, see The Office of Management and Budget Clearance Package Appendix E and F.
Flat Mail Envelope
Mail packages that include only the web invitation are traditionally mailed in a standard business
envelope. In 2020, in the first screener follow-up attempt, 50% of High Web households received their
web invitation in a document-sized flat mail envelope and the other 50% received the standard business
envelope. All mailings to High Paper households included a paper questionnaire and were mailed in the
larger flat mail envelopes. Attachment C includes examples of all mailing envelopes.
Priority Mail
Among the households that were mailed a paper topical questionnaire, 50% received their initial
invitation in a USPS Priority Mail Envelope. The other 50% received the traditional flat mail envelope.
Attachment C includes examples of all mailing envelopes.

Mailing Contents and Schedule
Data collection for the 2020 NSCH involved a series of mailings and nonresponse follow-up activities,
emphasizing questionnaire completion. Mailouts began Monday July 27, 2020 and continued until the
survey closeout on Friday January 22, 2021. The approach to data collection and nonresponse follow-up
was based on previous project experience and recommendations made by Dillman and colleagues
(2009): 12
•

Invitation letter. An initial invitation letter was mailed to all potential respondents providing
details about the study, a web URL with the login ID for accessing the web version of the survey
(which combined the screener and topical into a consolidated instrument), and a toll-free
number and email address for individuals to contact if there were questions or comments.

Dillman DA, Smyth JD, Christian LM. 2009. Internet, Mail and Mixed-Mode Surveys: The Tailored Design Method,
3rd edition. Hoboken, NJ: John Wiley & Sons.

12

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•

Additional mailings. Subsequent to the first invitation, the Census Bureau sent all remaining
non-responding addresses additional invitations. Addresses also received reminder postcards
after the first two mailings.

The production mailing schedule for the 2020 NSCH in Table 3 includes screener and topical mailing
events. The production mailout schedule consists of up to four screener mailings and two postcard
reminders across two groups (High Web and High Paper), and up to four topical mailings and a postcard
reminder to each of nine topical mailing groups (A – I below).
Table 3. Production Mailout Schedule
Date

Event

July 27, 2020 – August 3, 2020

Initial Mailing: High Web

July 27, 2020 – July 31, 2020

Initial Mailing: High Paper

August 3, 2020 – August 7, 2020

Pressure Sealed Postcard: High Web

August 3, 2020 – August 5, 2020

Pressure Sealed Postcard: High Paper

August 28, 2020

1st Follow-Up: High Web

September 8, 2020

1st Follow-Up: High Paper

September 4, 2020

2nd Pressure Sealed Postcard: High Web

September 14, 2020

2nd Pressure Sealed Postcard: High Paper

September 21, 2020

Topical Mailing 1

September 25, 2020

Topical Pressure Sealed Postcard: Group A

September 28, 2020

2nd Follow-Up: High Web

October 1, 2020

Topical Mailing 2

October 9, 2020

2nd Follow-Up: High Paper

October 9, 2020

Topical Pressure Sealed Postcard: Group B

October 20, 2020

Topical Mailing 3

October, 23, 2020

Topical Pressure Sealed Postcard: Group C

October 29, 2020

Topical Mailing 4

November 2, 2020

3rd Follow-Up: High Web

November 6, 2020

3rd Follow-Up: High Paper

November 6, 2020

Topical Pressure Sealed Postcard: Group D

November 12, 2020

Topical Mailing 5

November 20, 2020

Topical Pressure Sealed Postcard: Group E

November 24, 2020

Topical Mailing 6

December 4, 2020

Topical Pressure Sealed Postcard: Group F

December 11, 2020

Topical Mailing 7

December 18, 2020

Topical Pressure Sealed Postcard: Group G

December 22, 2020

Topical Mailing 8

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Date

Event

December 30, 2020

Topical Pressure Sealed Postcard: Group H

January 4, 2021

Topical Mailing 9

January 11, 2021

Topical Pressure Sealed Postcard: Group I

January 22, 2021

Survey Closeout

Initial Screener Invitation
The initial mailing included the following treatments:
• Screener cash incentives
• Mixed-mode (High Paper)
• Mailing package redesign
Postcard reminders were mailed one week after initial mailings.
Screener Non-response Follow-up Mailings
The screener non-response follow-up mailings included the following treatments:
• Mixed-mode (High Paper)
• Mailing package redesign
• Flat mail envelope (first follow-up only)
Postcard reminders were mailed one week after the first follow-up mailing. The screener data collection
strategy included three attempts for non-response follow-up. 13 Addresses remained in their mailing
package redesign group assignment through data collection and their mode assignment (High Paper or
High Web) unless a High Web household requested a paper questionnaire before the first follow-up
mailing.
Topical Questionnaire
The topical questionnaires were only sent to households that returned a complete paper screener
questionnaire, had eligible children in the house, and had not submitted a questionnaire by web. Topical
mailings included the following treatments:
•
•
•

Topical cash incentives (initial attempt only)
Mailing package redesign
Priority Mail envelope (initial attempt only)

There were nine pre-determined mailing dates (1-9) for topical questionnaires. When respondents
returned a complete paper screener, they were assigned to the next planned mailing date’s initial
Addresses stopped receiving mailings if the residents submitted a web survey, returned a complete paper
screener, explicitly refused to participate, or if the address was out-of-scope (i.e., not an occupied residence). The
address also received fewer mailings if the USPS determined the address to be undeliverable as addressed.

13

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mailing group (A-I; see Table 4). There were up to three attempts for non-response follow-up depending
on the respondent’s group assignment. The number of follow-up mailings was constrained by the data
collection window, with later groups receiving fewer attempts; groups A-C received three follow-ups,
groups D and E received two, groups F and G received one, and groups H and I did not receive follow-up
mailings. All topical mailings included a paper topical questionnaire.
Postcard reminders were mailed one week after the initial mailing for that household.
Table 4. Topical Mailings and Topical Mailing Groups
Mailing
Mailing 1
Mailing 2
Mailing 3
Mailing 4
Mailing 5
Mailing 6
Mailing 7
Mailing 8
Mailing 9

Initial
Group A
Group B
Group C
Group D
Group E
Group F
Group G
Group H
Group I

2020 National Survey of Children’s Health

1st Follow-up

2nd Follow-up

3rd Follow-up

Group A
Group B
Group C
Group D
Group E
Group F
Group G

Group A
Group B
Group C
Group D
Group E

Group A
Group B
Group C

U.S. Census Bureau

21

Response Analysis
Response Rates
Table 5 provides a summary of the survey completion counts. 93,500 14 households completed a
screener portion of the survey. Of those, 51,107 reported children and are included on the Screener
data file.
Complete and sufficient partial topical questionnaires are included on the Topical Public Use File. Of the
51,107 screened households with children, 42,777 returned a complete or sufficient partial topical
survey. In 2020, 90.4% of respondents completed the survey using the web instrument and 9.6% of
respondents completed the survey using the paper instruments.
Table 5. 2020 Final Dispositions (Unweighted)
Final Disposition
Count a
Total Cases
240,000a
Occupied Households (Estimated)
198,000 a
Households with Children (Estimated)
112,000 a
Completed Screeners
93,500 b
Screeners with Children
51,107a
Completed Topicals
42,777a
a
Rounded to the nearest thousand
b
Rounded to the nearest five hundred
For the purposes of calculating response rates, all sampled addresses were assigned screener and
topical outcomes codes. These outcomes can be summarized as not eligible, eligible but not complete,
complete or eligibility unknown.
For some addresses, there was not sufficient correspondence to determine if the address was eligible to
complete the screener or topical questionnaires. These addresses were classified as unresolved. Among
these addresses, we estimated the share that were occupied residences using the Household Rate,
which is the proportion of resolved addresses that are occupied residences. 15 We also estimated the
Child Rate, which is the share of those households that include children, based on the proportion of
households that have children by state and stratum in the 2018 American Community Survey (ACS). The
product of the Household Rate and Child Rate is the Eligibility Rate (e), the estimated proportion of
unresolved addresses that are households with children. Using this approach, we estimated that 87%

Rounded to the nearest five hundred based on the U.S. Census Bureau disclosure avoidance practices.
Specifically, we used the midpoint between the Household Rate including undeliverable addresses (the
proportion of all resolved addresses that are occupied residences) and the Household Rate excluding undeliverable
addresses (UAAs) by state and stratum. Because UAAs are identified by the U. S. Postal Service, it is assumed that
UAAs are identified at a higher rate than other noneligible addresses (businesses, vacant residences, etc.) that
must be self-identified. The midpoint assumes that there are some UAAs still unresolved but at a lower rate than
they appear among the resolved addresses.

14

15

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(weighted) of unresolved addresses were households, and 40% (weighted) of those were households
with children.
𝑒𝑒 = 𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻ℎ𝑜𝑜𝑜𝑜𝑜𝑜 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 ∗ 𝐶𝐶ℎ𝑖𝑖𝑖𝑖𝑖𝑖 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅

Three different response rates were calculated based on the estimated proportion of eligible addresses
that completed the screener and topical questionnaires. Definitions of completion and the calculation of
these three response rates are detailed below.
Screener Completion Rate
The Screener Completion Rate (SCR) is the estimated proportion of households (occupied residences)
that completed a screener. A completed screener had to 1) be returned from a sampled address, and 2)
indicate that there were no children present or provide a valid age for at least one child. The
denominator includes both screened households and the number of unresolved addresses that are
estimated to be households.
𝐶𝐶𝐶𝐶𝑚𝑚𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆
𝑆𝑆𝑆𝑆𝑆𝑆 =
𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝐻𝐻𝐻𝐻𝐻𝐻 + (𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 ∗ 𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻ℎ𝑜𝑜𝑜𝑜𝑜𝑜 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅)
Topical Completion Rate
The Topical Completion Rate (TCR) is the estimated proportion of households with children that
returned a topical questionnaire, either complete or sufficient partial. Completed topical
questionnaires have valid answers for at least 40 of 50 test questions. Also, at least one item in
Section K (family income, household and family count) must be completed, or the respondent
submitted the topical portion of the web instrument. Sufficient partial topical questionnaires have
valid answers for at least 25 of 50 test questions. Also, at least one item in Section H or beyond
must be completed, or the respondent submitted the topical portion of the web instrument. The
denominator includes both screened households with children and the number of unresolved
addresses that are estimated to be households with children (Unresolved Addresses * e).
𝑇𝑇𝑇𝑇𝑇𝑇 =

𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇
𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝐻𝐻𝐻𝐻𝐻𝐻 𝑤𝑤𝑤𝑤𝑤𝑤ℎ 𝐶𝐶ℎ𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 + (𝑈𝑈𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 ∗ 𝑒𝑒)

Interview Completion Rate and Overall Response Rate
The Interview Completion Rate (ICR) and Overall Response Rate (ORR) account for the multi-stage
design of the NSCH. They are the products of two (for ICR) or three (for ORR) response rate metrics that
are each consistent with the American Association for Public Opinion Research (AAPOR) standards 16.
The ICR is the probability a household progresses through the screener and topical portions of the
survey.
𝐼𝐼𝐼𝐼𝐼𝐼 = 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 ∗ 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅
The American Association for Public Opinion Research. 2016. Standard Definitions: Final Dispositions of Case
Codes and Outcome Rates for Surveys. 9th edition. AAPOR.

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The Screener Conversation Rate is the proportion of resolved households that completed the screener.
𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 =

𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜

The Topical Conversation Rate is the proportion of screened households with children that completed a
topical.
𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 =
𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑤𝑤𝑤𝑤𝑤𝑤ℎ 𝐶𝐶ℎ𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
The Overall Response Rate (ORR) is the probability an address progresses from resolution to screener
complete to topical complete, as given by the equation below,
𝑂𝑂𝑂𝑂𝑂𝑂 = 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 ∗ 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 ∗ 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅

where the Resolution Rate is the proportion of addresses in sample that were resolved as occupied
households. In 2020, the weighted Resolution Rate was 52.2%.
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 =

𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴

Table 6 lists the weighted rate for each of the four response metrics discussed above. A breakdown of
the response rates by state is provided in Attachment D.
Table 6. 2020 NSCH Weighted Response Rates
Metric
Rate
Screener Completion Rate
47.1%
Topical Completion Rate
36.4%
Interview Completion Rate
81.2%
Overall Response Rate
42.4%

Item-Level Response
The item-level response rate is the proportion of item-eligible respondents that provided a valid answer
to a particular item. Many items were applicable to a subset of survey respondents only; for example,
some questions were applicable to children in a specific age range. In that case, the denominator for the
item-level response rate is the count of children in the eligible age range, and the numerator is the
count of those children with valid responses.
In some cases, it is uncertain if the child was eligible for an item due to nonresponse on a preceding
item. For example, before asking about the severity of certain conditions, we asked if the child currently
had the condition. The severity item was applicable if the child currently had the condition, and it was
not applicable if the child did not currently have the condition. If the respondent chose to skip the
current condition filter item, we cannot know definitively if the severity item was applicable or not.

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We account for this situation in the item-level response rate by assigning eligibility to cases with
unknown eligibility equal to the proportion of cases that were eligible when eligibility was known. For
example, if 10% of respondents reported that the child did have the condition currently, and so were
eligible for the severity follow-up question, the denominator for the severity item response rate
becomes
# 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 + (# 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈 ∗ .1)

Across all survey items, more than 98% of response opportunities produced a valid response. Items that
require a write-in response, that require respondents to follow a skip pattern, and are near the end of
the survey tend to have higher nonresponse. Table 7 lists the 35 variables with the lowest item-level
response rates. The list predominantly reflects items that are at the end of a skip pattern and are onpath for few respondents (e.g., CYSTFIB_SCREEN), items that require a write-in response (e.g.,
A2_LIVEUSA), and items near the end of the survey (e.g., A2 items). 17
Table 7. Lowest Item-Level Response Rates
Response
Rate

On-Path
(%)

Cystic Fibrosis Newborn Screening

86.0%

0.1%

K2Q35A_1_YEARS

Autism ASD - First Told Age in Years

91.0%

3.0%

BLOOD_DESC

Blood Disorder Severity Description

93.1%

0.5%

HCEXTENT

Health Affected Ability - Extent

93.4%

30.4%

A2_LIVEUSA

Adult 2 - Come to Live in the United States (Year)

94.8%

13.1%

ACE12

Treated Unfairly Because of their Sexual Orientation

95.8%

71.6%

LIVEUSA_MO

How Long Living in the United States - Months

95.8%

3.4%

K5Q22

Arrange or Coordinate as Much Help As Wanted

95.8%

4.2%

LIVEUSA_YR

How Long Living in the United States - Years

95.9%

3.4%

A2_DEPLSTAT

Adult 2 - Deployment Status

95.9%

5.7%

A2_BORN

Adult 2 - Where Born

95.9%

84.1%

A2_AGE

Adult 2 - Age in Years

96.2%

84.1%

ACE8

Lived with Mentally Ill

96.2%

100.0%

ACE9

Lived with Person with Alcohol/Drug Problem

96.2%

100.0%

ACE7

Victim of Violence

96.2%

100.0%

ACE10

Treated Unfairly Because of Race

96.2%

100.0%

ACE6

Child Experienced Adults Slap, Hit, Kick, Punch Others

96.2%

100.0%

A2_PHYSHEALTH

Adult 2 - Physical Health

96.3%

84.1%

Variable

Description

CYSTFIB_SCREEN

17

This table does not include the six poverty status implicates (FPL1-FPL6). Values for these items are derived from several
survey items, and partial responses are used to inform the multiple imputation. For comparison, 19.7% of respondents do not
provide sufficient information to deduce the poverty status from survey responses alone.
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A2_EMPLOYED

Adult 2 - Current Employment Status

96.3%

84.1%

A2_MENTHEALTH

Adult 2 - Mental or Emotional Health

96.3%

84.1%

A2_MARITAL

Adult 2 - Marital Status

96.3%

84.1%

STRENGTHS

Facing Problems - How Often Draw on Strengths

96.3%

100.0%

K9Q96

Other Adult Child Can Rely On For Advice

96.3%

71.6%

ACE5

Child Experienced - Parent or Guardian Time in Jail

96.3%

100.0%

A1_LIVEUSA

Adult 1 - Come to Live in the United States (Year)

96.3%

14.0%

BIRTHWT

Birth Weight Status

96.4%

100.0%

BIRTHWT_L

Birth Weight is Low (<2500g)

96.4%

100.0%

BIRTHWT_VL

Birth Weight is Very Low (<1500g)

96.4%

100.0%

BIRTHWT_OZ_S

Standardized Birth Weight, Ounces

96.4%

100.0%

WKTOSOLVE

Facing Problems - How Often Work Together

96.4%

100.0%

K10Q41_R

Child Is Safe at School

96.4%

71.6%

BREASTFEDEND_MO_S

Stopped Breastfeeding - Months (Standardized)

96.4%

21.3%

BREASTFEDEND_WK_S

Stopped Breastfeeding - Weeks (Standardized)

96.4%

21.3%

BREASTFEDEND_DAY_S

Stopped Breastfeeding - Days (Standardized)

96.4%

21.3%

A2_GRADE

Adult 2 - Highest Completed Year of School

96.4%

84.1%

Treatment Groups and Response
This section reviews response patterns based on the treatment group assignments:
•
•
•
•
•
•

Screener Cash Incentives
Topical Cash Incentives
Mixed Mode (High Paper) vs. Web-Push (High Web)
Mailing Package Redesign
Flat Mail Envelope
Priority Mail Envelope

Screener Cash Incentives
In the initial mailing for screener questionnaires, 90% of the sample received a small denomination bill
as an incentive to complete the survey, 30% receiving a $2 bill and 60% a $5 bill.
The unconditional cash incentives are included with the initial invitation to encourage households to
respond. The results of the intervention are reported in Table 8. Eligible households that received a $5
incentive were more likely to complete the Screener and Topical questionnaires than households that
received a $2 incentive or no incentive. Eligible households that received a $2 incentive were more likely
to complete the Screener questionnaire and Topical questionnaire than households that received no
incentive. Extrapolating from the results below and the estimate in Table 5 that the 2020 sample
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included 112,000 households with children, we estimate that 5,500 fewer households would have
completed the topical questionnaire if we did not use screener incentives.
Table 8. Data Collection Costs and Completed Questionnaires by Screener Incentive
Screener Cash
Incentive
Group
Total
No Incentive
$2 Incentive
$5 Incentive

Average Cost
per Completed
Screener
$22.89
$16.36
$19.82
$25.28

Percent of Eligible
Households that
Completed a Screener
46.8%
41.9%
45.7%
48.2%

Average Cost
per Completed
Topical
$53.51
$40.40
$47.28
$58.25

Percent of Eligible
Households that
Completed a Topical
38.2%
33.3%
37.0%
39.6%

The distribution of screener incentives changed between 2019 and 2020. In 2019, 45% of addresses
received a $2 incentive and 45% of addresses received a $5 incentive. In 2020, the share of addresses
receiving a $5 incentive increased to 60% and the share receiving $2 was decreased to 30%. The net
impact of this change is that 15% of the sample had their incentive amount increase by $3, and the
average cost per case increased by $0.45 (15% x $3). The larger incentive motivated more households to
respond, though the magnitude of the change, by cost and impact, was relatively small. We estimate
that increasing the share of households receiving the $5 incentive produced 700 to 800 completed
screener questionnaires and 400 to 500 completed topical questionnaires.
Topical Cash Incentive
For households who were mailed their first paper topical questionnaire, 90% received a $5 bill while the
other 10% did not receive an incentive.
Table 9. Data Collections Costs and Returns by Topical Incentive
Incentive
Average Cost per
Group
Completed Topical
Completion Rate*
Total
$56.44
51.2%
No Incentive
$60.48
41.2%
$5 Incentive
$56.09
52.3%
*Percent of households that were mailed a paper topical invitation that
subsequently completed a topical interview.

Households that received a $5 incentive were more likely to complete the topical questionnaire than
households that received no incentive (see Table 9). Also, by reducing the number of non-response
follow-up mailings, the topical incentive reduced the cost of data collection versus the control group. In
other words, the topical incentive increased the survey’s response rate while also reducing the cost of
data collection.

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Incentives and Non-Response Bias
In past cycles of the NSCH, cash incentives were relatively more effective among groups that were
otherwise less likely to respond. 18 The incentives did not have the same effect in 2020. For example,
Table 10 shows the incentive effect as the ratio of the probability of screener and topical response with
and without the incentive by education, race and poverty/income. The cash incentive significantly
increased screener and topical response for all groups. With the screener incentive, the incentive effect
was larger for less educated households, Black households (compared to White households), and
households in poverty, but the difference was not statistically significant. Likewise, the topical incentive
did not have a significantly larger effect among lower-responding household types.
The primary difference between 2019, when incentives were relatively more effective for the lowerresponding household types, and 2020 is in the base level of response from these households.
Comparing 2019 to 2020, the high school or less households in the control group increased their rate of
response by 5.3%, the Black alone households by 12.2% and the households in poverty by 9.9%. The rate
of response for the control group as a whole increased 4.9%. In other words, the impact of the
incentives on reducing potential nonresponse bias decreased between 2019 and 2020 because the need
for the incentives to reduce potential nonresponse bias also decreased.
Table 10. Response Odds Ratios (Incentive versus No Incentive) by Education, Race, and Income

Education
High School or less
College or more
HS vs. College
Race
Black alone
White alone
Black vs. White
Poverty Status
Poverty
Income > $100k
Poverty vs. Income >
$100k

Screener
P($2 incentive) /
P($5 incentive) /
P(control)
P(control)
109.4% *
115.8% *
108.8% *
114.5% *
+0.6%
+1.3%

Topical
P($5 incentive) /
P(control)
125.2% *
128.2% *
-3.0%

109.2% *
109.7% *
+0.5%

115.2% *
118.4% *
+3.2%

125.1% *
125.4% *
+0.2%

108.5% *
108.3% *

115.0% *
114.1% *

126.8% *
129.3% *

+0.1%

+0.9%

-2.5%

* H 0 : P(incentive)/P(control) <= 1, p<0.05; † H 0 : Difference <= 0, p<0.05

NSCH 2019 Methodology Report (https://www2.census.gov/programs-surveys/nsch/technicaldocumentation/methodology/2019-NSCH-Methodology-Report.pdf)
18

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Mixed Mode (High Paper) vs. Web Push (High Web)
The mixed-mode data collection strategy used with the High Paper addresses encourages more
households to respond by mail, which has two disadvantages compared with web response. 1) Mailout/mail-back data collection is more costly than web. 2) Households with children that respond to the
screener questionnaire online are more likely to complete the topical questionnaire than those that mail
back a paper screener questionnaire. In 2020, the data collection cost per reported household with
children was 89% higher for High Paper households than Low Paper households. Only 74% of those High
Paper households with children completed the topical questionnaire versus 83% of the Low Paper
households. It is for this reason that the High Paper mixed mode strategy is used only for those
addresses that are most likely to respond by mail and not be web.
Mailing Package Redesign
30% of the sample received redesigned mail materials throughout data collection while the remaining
70% received the traditional NSCH envelope and accompanying materials. Color printing in the
redesigned materials slightly increased data collection costs (approximately $0.87 per address) and
addresses in the redesigned materials experiment were less likely to respond (-4.8% screener
questionnaires completed).
Flat Mail Envelope
In the first follow-up for screener questionnaires, 50% of nonresponding households in the High Web
group received a flat mail envelope while the other 50% received the standard business envelope.
Ultimately, the flat mail envelope added marginal cost, and response rates between the test and control
group were virtually identical.
Priority Mail Envelope
Among the households that were mailed a paper topical questionnaire, 50% received their initial
invitation in a USPS Priority Mail Envelope. The other 50% received the traditional NSCH envelope. The
Priority Mail Envelope added significant cost (approximately $4.13 per address) and did not significantly
increase response over the control group – 50.8% for the Priority group, 49.7% for the control group.
That said, there was significant variation in the effect of the envelope across different groups.
Specifically, addresses that responded more quickly using the paper screener questionnaire were more
likely to complete the topical questionnaire in the traditional envelope. Late-responding addresses were
more likely to complete the topical questionnaire if the Priority Mail Envelope. That said, the Priority
Mail envelope was less cost effective and reliable than the topical incentive.
The Shift to Web Response in 2020
The 2020 NSCH saw a significant increase in the share of respondents using web response. Between
2016 and 2019, 58.7% (NSCH 2017) to 66.0% (NSCH 2019) of screener respondents used web, and 75.9%
(NSCH 2017) to 80.6% (NSCH 2016) of topical respondents used web. In 2020, 76.5% of screener
respondents and 90.4% of topical respondents used web. There are several potential explanations for
this shift in respondent-selected response mode. First, the 2020 Census included a full online response
option, and more than half of American households responded online, thus increasing the likelihood
that respondents had previous experience with web-based surveys. Second, the COVID-19 pandemic
29
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forced many Americans to conduct more of their lives – school, work, shopping, socializing – online. In
turn, we can assume that more Americans were more comfortable responding to a survey online.
To ensure that state and national estimates from the 2020 NSCH are representative and comparable to
previous years, the data were evaluated for potential bias from nonresponse and changes in sample
composition. This analysis considered differences between respondents and nonrespondents, and
effectiveness of weighting adjustments to correct for those differences. The 2020 NSCH Nonresponse
Bias Analysis located on the Technical Documentation Page did not find strong or consistent evidence of
nonresponse bias.
Furthermore, the Overall Response Rate for the NSCH was unchanged from 2019 to 2020, and there was
increased response in 2020 from household types that are often underrepresented among survey
respondents. For example, the unweighted shares of children that were Hispanic and Black alone were
marginally higher in 2020 than in any year since the NSCH redesign.
An additional evaluation considered other changes in sample composition and their impact on data
quality. Response distributions for all items on the 2020 NSCH microdata file were reviewed
independently and against the 2019 NSCH by response mode and child age, with and without weighting
adjustments. This analysis did not find evidence that changes in sample composition, including response
mode, caused substantial changes in response distributions after weighting adjustments were applied.
Taken together, these analyses indicate that state and national estimates from the 2020 NSCH are
representative and comparable to previous years.

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Data Processing
Data were processed and edited to ensure data quality and respondent confidentiality.

Unduplication
All nonresponding households were offered two modes, web and paper, for completing the survey. In
some cases, respondents utilized both options. In these cases, we selected one response, web or paper,
to include in the data file. We chose the response to include based on the type of return and the level of
completeness. Completed web returns were always chosen over completed paper returns. However,
completed paper returns were chosen over partial web survey returns. The web/paper unduplication
hierarchy is detailed in Table 11.
Table 11. Unduplication Criteria for both Web and Paper Returns
Order Chosen

Type of Return

1

Completed web survey - Household with children

2

Completed paper screener and topical

3

Completed web survey - Household w/o children

4

Completed paper screener - Household w/o children

5

Partially completed web survey

6

Out of scope paper return

7

Refusal paper return, Hard Refusal

8

Incomplete, Duplicate

9

Blank, Soft Refusal

10

Deceased

11

Undeliverable address (UAA) with address correction – mail forwarded, UAA
with address correction

12

UAAs, Forwarding Order Expired, Moved out of U.S.

13

Default

14

Blank form

Multiple follow-up mailings included paper questionnaires, so it was also possible that respondents
received and returned more than one questionnaire. In these cases, one return was selected to
represent that case in the data file. The paper/paper unduplication hierarchy is detailed in Table 12.

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Table 12. Unduplication Criteria for Two Paper Returns
Order Chosen

Type of Return

1

Completed paper screener/topical - Household with children

2

Completed paper screener - Household w/o children

3

Out of scope paper return

4

Refusal paper return, Hard Refusal

5

Incomplete, Duplicate

6

Blank, Soft Refusal

7

Deceased

8

UAA with address correction – mail forwarded, UAA with address correction

9

UAAs, Forwarding Order Expired, Moved out of U.S.

10

Default

11

Blank form

Paper to Web Standardization
Responses were standardized across web and paper so they could be appended in a single data file.
Although survey questions had the same valid values for the paper and web instruments, sometimes the
values output for the paper questionnaire did not match the output from the web survey instrument.
For instance, any questions that included a list of checkboxes where the respondent was instructed to
“mark (X) ONE box” differed between paper and web. The web instrument had the ability to prevent the
selection of more than one checkbox via a radio button, whereas a paper respondent could mark more
than one box even if the question explicitly said not to. Since all data from the paper instruments is
captured for processing, each of the response option checkboxes have their own associated output
variable. Therefore, prior to appending web and paper responses into a single data file, paper responses
were reformatted to the proper valid values.

Data Edits
The 2020 NSCH raw output was processed to manage inconsistent and invalid responses in nine
sequential steps:
•

Stop Process Edit. A case is removed from the data file if the case fails address verification (the
respondent indicates that their address does not match the address on file), the respondent
indicates that there are no children in the household, or the respondent does not complete a
screener for a household with children. The cases are not eligible to be included on a NSCH data
file, so are removed from processing.

•

Not in Universe Edit. An item is not in universe if it is not included in the instrument the
respondent received. Some items are unique to web or paper, and others are specific to a

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version of the topical instrument, T1, T2, or T3. The value for an item that is not in universe is
set to ‘.N’.
•

Range Edit. If a value falls outside the bounds of a defined minimum and maximum for that
item, the value is replaced with an indicator that the response is missing. The minimum and
maximum are selected to represent a reasonable range of possible responses to the item.

•

Backfill Edit. The backfill edit imputes values to some items based on responses to subsequent
items that necessarily indicate the correct response to the edited item. Backfill edits apply
almost exclusively to paper questionnaires, which cannot prevent a respondent from skipping a
root item but answering follow-up questions. For example, INCWAGES is a binary item that
filters respondents on whether the family did (INCWAGES=1) or did not (INCWAGES=2) receive
wage or salary income. If a respondent does not answer INCWAGES, but provides a valid and
non-zero value for INCWAGES_AMT, the dollar amount of wage and salary income, then it is
necessarily correct that INCWAGES=1.

•

Yes/No Edit. The NSCH includes several series that ask respondents to select all applicable items
from a list. These series may or may not allow the respondent to answer in the negative,
indicating that the item is not applicable. In most cases, if a respondent answers in the
affirmative (=1) to at least one item in the series, it is assumed that all other items in the series
do not apply (=2) unless otherwise noted. If a respondent is only able to respond in the
affirmative, and the items in the series are not comprehensive (e.g., they do not include an
“Other” option), then it is assumed that all unanswered items do not apply (=2) without
imposing the requirement that at least one item is answered in the affirmative.

•

Consistency Edit. If responses to two items in the survey are fundamentally inconsistent, one
response is maintained and the other is removed and changed to missing. Most consistency
edits require that a child does not experience a life event at an age greater than her current age.
Because the instrument generally trends from more general, fundamental information to more
specific, priority is given to the item that appears first in the instrument.

•

Legitimate Skip Edit. Unlike the ‘Not in Universe Edit’, the legitimate skip edit applies to items
that are on the respondent’s instrument, but not on path. The value for an item that is in
universe but not on path is set to ‘.L’.

•

Missing in Error Edit. If an item is in universe (does not equal .N), is on path (does not equal .L),
but does not hold a valid value, that item is missing in error, identified as ‘.M’.

•

Disclosure Edit. Some survey responses, if published, could compromise a respondent’s
confidentiality. Disclosure edits involve removing entire items (e.g., child’s name) or suppressing
rare or unique values (e.g., top codes on the family poverty ratio). Census disclosure avoidance

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standards make reference to weighted and unweighted cell counts (i.e., the number of children
with a characteristic or set of characteristics), the size of the underlying population (e.g., the
number of children in Kentucky Metropolitan Statistical Areas), and the existence of outside
data sources that could be matched to the NSCH (e.g., a registry of children diagnosed with
Cerebral Palsy).
Edits were applied in two stages. In the first stage, edits for screener items were applied to completed
screeners with children. When these edits were completed, cases that did not return a completed
topical were removed from edits, and the second stage edits to topical items were applied.

Recoded and Standardized Variables
Standardized Variables
Several questions in the 2020 NSCH allowed respondents to provide an answer using more than one unit
(e.g., years and months) and to choose from two systems of units (e.g., imperial or metric). In these
cases, we provide standardized variables that convert responses across units and systems to a single
unit. See Table 13 for a list and description of these variables.
Table 13. Standardized Variables
Variable

Description

Units

BIRTHWT_OZ_S

Child birth weight

Ounces

BREASTFEDEND_DAY_S

Stopped breastfeeding

Days

BREASTFEDEND_WK_S

Stopped breastfeeding

Weeks

BREASTFEDEND_MO_S

Stopped breastfeeding

Months

FRSTFORMULA_DAY_S

First fed formula

Days

FRSTFORMULA_WK_S

First fed formula

Weeks

FRSTFORMULA_MO_S

First fed formula

Months

FRSTSOLIDS_DAY_S

First fed solids

Days

FRSTSOLIDS_WK_S

First fed solids

Weeks

FRSTSOLIDS_MO_S

First fed solids

Months

Derived and Recoded Variables
A number of variables on the public use data files are derived from a set of items on the survey or a
recoded version of a single item. These variables are listed in Table 14.
Table 14. Derived and Recoded Variables
Variable

Description

Derived from

AGEPOS4

Birth position of the selected child relative to
other children in household

C_AGE_YEARS
C_AGE_MONTHS

TOTMALE

Count of male children in household

C_SEX

TOTFEMALE

Count of female children in household

C_SEX

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Variable

Description

Derived from

C_CSHCN

Special Health Care Needs (SHCN) status

C_K2Q10 - C_K2Q23

SC_CSHCN

SHCN status of selected child

C_CSHCN

TOTCSHCN

Count of children with SHCN

CSHCN

TOTNONSHCN

Count of children that do not have SHCN

C_K2Q10 - C_K2Q23

TOTAGE_0_5

Count of children 0 to 5 years old in household

C_AGE_YEARS

TOTAGE_6_11

Count of children 6 to 11 years old in household

C_AGE_YEARS

TOTAGE_12_17

Count of children 12 to 17 years old in household

C_AGE_YEARS

SC_AGE_LT4

Age of selected child (less than 4 months)

SC_AGE_YEARS
SC_AGE_MONTHS

SC_AGE_LT6

Age of selected child (less than 6 months)

SC_AGE_YEARS
SC_AGE_MONTHS

SC_AGE_LT9

Age of selected child (less than 9 months)

SC_AGE_YEARS
SC_AGE_MONTHS

SC_AGE_LT10

Age of selected child (less than 10 months)

SC_AGE_YEARS
SC_AGE_MONTHS

C_RACER

Race of child

C_RACE_R

C_RACEASIA

Asian race category is included for the following
states: CA, HI, MA, MD, MN, NJ, NV, NY, VA, WA

C_RACE_R

C_RACEAIAN

American Indian/Alaska Native race category is
C_RACE_R
included for the following states: AK, AZ, NM, MT,
ND, OK, SD

C_HISPANIC_R

Hispanic origin

C_HISPANIC

SC_RACER

Race of selected child

SC_RACE_R

SC_RACEASIA

Asian race category is included for the following
states: CA, HI, MA, MD, MN, NJ, NV, NY, VA, WA
(Selected Child)

SC_RACE_R

SC_RACEAIAN

American Indian/Alaska Native race category is
SC_RACE_R
included for the following states: AK, AZ, NM, MT,
ND, OK, SD (Selected Child)

SC_HISPANIC_R

Hispanic origin of selected child

SC_HISPANIC

HOUSE_GEN

Parental nativity

BORNUSA
A1_RELATION
A1_BORN
A2_RELATION
A2_BORN

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Variable

Description

Derived from

FAMILY_R

Family structure

A1_RELATION
A2_RELATION
A1_MARITAL
A2_MARITAL
A1_SEX
A2_SEX

CURRINS

Current health insurance coverage status

K3Q04_R
CURRCOV
K12Q03, K12Q04,
K12Q12, TRICARE,
HCCOVOTH, K11Q03R

INSTYPE

Type of insurance

CURRINS
K12Q03, K12Q04,
K12Q12, TRICARE,
HCCOVOTH, K11Q03R

INSGAP

Health insurance coverage over the past 12
months

K3Q04_R, CURRINS

FPL_I1-FPL_I6

Family poverty ratio

FAMCOUNT
TOTINCOME

HIGRADE

Highest level of education for reported adults
(three categories)

A1_GRADE
A2_GRADE

HIGRADE_TVIS

Highest level of education for reported adults
(four categories)

A1_GRADE
A2_GRADE

BIRTHWT

Birth weight status

BIRTHWT_OZ_S

BIRTHWT_L

Low birth weight (<2500g)

BIRTHWT_OZ_S

BIRTHWT_VL

Very low birth weight (<1500g)

BIRTHWT_OZ_S

BMICLASS

Body Mass Index

WEIGHT_*
HEIGHT_*

Specifications of Select Derived Variables
The 2020 NSCH reports several derived variables that include information on the child’s family status.
This includes Family Poverty Ratio (FPL), Household Nativity (HOUSE_GEN), and Family Structure
(FAMILY_R).
•

Family Poverty Ratio (FPL) - The family poverty ratio is calculated as the ratio of total family
income to the family poverty threshold and reported as a rounded percentage. Respondents
reported total family income in item K4 on the paper instrument: “The following question is
about your 2019 income. Think about your total combined family income IN THE LAST
CALENDAR YEAR for all members of the family. What is that amount before taxes?” Additional
text instructed respondents to include all money incomes, for example, social security,
dividends, and child support. Responses to K4 were edited for consistency against answers in K3,

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a series of questions about specific sources of income. Finally, missing or invalid responses were
replaced with multiply imputed values.
The family poverty threshold is derived from the Census Bureau’s poverty thresholds.
Thresholds vary by family size and the number of related children under 18 years old. They do
not vary across geographies. Family size was reported in K2 of the paper instrument. Missing or
invalid values were imputed. The number of related children was determined by the number of
children reported in the screener.
To protect the confidentiality of respondents, only FPL is reported in the Public Use File; total
family income and the family poverty threshold are not included. Further, FPL is top and bottom
coded. Reported values range from 50 (total family income is 50% of the family poverty
threshold) to 400 (total family income is 400% of the family poverty threshold). Values beyond
this range are reported as 50 or 400, respectively.
•

Household Nativity (HOUSE_GEN) - Household nativity is determined by the birth location of the
child (BORNUSA) and parents (A1_BORN and A2_BORN). If the child was born outside of the U.S.
and all reported parents were born outside of the U.S., the household is reported as a 1st
generation household. Second generation households have members born both inside and
outside of the U.S. For example, the child was born in the U.S. and at least one parent was born
outside of the U.S., or the child was born outside of the U.S. and one of two parents was born in
the U.S. Finally, in 3rd+ generation households, all parents were born in the U.S. The fourth
category, “Other”, captures households with insufficient information about the nativity of the
parents.

•

Family Structure (FAMILY_R) - A family structure variable uses the reported information on the
child’s primary caregivers to organize households into common types. Notably, the NSCH
collects information on only two adults in the household and requires only that the two adults
be primary caregivers of the child. As a result, in multigenerational households, this can mean
that a biological, adoptive, or stepparent is not reported.
Further, respondents do not report their relationship to other adult members of the household,
only to the child; consequently, we may know that the two reported adults are married, but we
do not know if they are married to each other. Instead of making assumptions about the
relationship of the reported adults with each other, the family structure variable depends only
on the number of adults, their relationship to the child, and their individual marital statuses. For
example, a reported value of 1 for FAMILY means that the two reported adults are
biological/adoptive parents of the child and they are currently married; one may assume that
they are married to each other, but in some cases that will not be true.
Two family structure categories (FAMILY_R=5 and 6) are also defined by the sex of the
respondent. In these cases, it is specified that the responding caregiver is female (5) or male (6)
and that no other parents (biological, adoptive, or step) are in the household.

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The 2020 NSCH reports several variables that include information on the child’s health insurance status
and insurance type. We strongly recommend that data users interested in current health insurance
status and insurance type use the derived variables CURRINS (Currently Insured), INSGAP (Gaps in
Coverage), and INSTYPE (Insurance Type) in their analyses.
•

Currently Covered (CURRINS) - CURRINS is derived primarily from the respondent-reported
values in K3Q04_R (Health Insurance Coverage – Past 12 Months) and CURRCOV (Health
Insurance Coverage – Currently Covered). We indicate that the child is currently insured
(CURRINS=1) if the respondent reported that the child had coverage for all of the last 12 months
(K3Q04_R=1) or reported that the child is currently covered (CURRCOV=1), but with an
important caveat. If the respondent reported that the child is currently insured but reported
only Indian Health Service or health care sharing ministry as the type of coverage, we indicate
that the child does not have current insurance coverage (CURRINS=2). Consequently, a
respondent may report that a child is insured, but we consider that the child is not insured.

•

Gaps in Coverage (INSGAP) - INSGAP is derived primarily from the respondent reported values in
K3Q04_R (Health Insurance Coverage – Past 12 Months) and CURRCOV (Health Insurance
Coverage – Currently Covered). We indicate that the child had consistent coverage (INSGAP=1) if
the respondent reported that the child had coverage for all of the last 12 months (K3Q04_R=1)
but with an important caveat. If the respondent reported that the child is currently insured but
reported only Indian Health Service or health care sharing ministry as the type of coverage, we
indicate that information as to the consistency of the child’s coverage is missing (INSGAP=.M).

•

Insurance Type (INSTYPE) - INSTYPE is derived from CURRINS (Currently Insured) and respondent
answers to questions on the coverage type: K12Q03 (Current/Former Employer or Union),
K12Q04 (Directly Purchased), K12Q12 (Government Assistance Plan), TRICARE (TRICARE or other
military health care), K11Q03 (Indian Health Service), and HCCOVOTH_WRITEIN (Other Type,
Write-in). Any insurance reported as coming from an employer or union, directly purchased,
TRICARE or other military health care, or the Affordable Care Act is considered private. Coverage
from any government assistance plan is considered public. Both the private and public coverage
categories reflect a single reported source of coverage; a combined category for children with
both public and private coverage is also included.

In addition, Health Insurance write-in (HCCOVOTH_WRITEIN) responses were back-coded to flag public
and private insurance types, religious health care sharing ministry, and Indian Health Service coverage.
These flags were used in the derivation of CURRINS and INSTYPE. To protect respondent confidentiality,
answers to HCCOVOTH_WRITEIN are not reported in the Public Use File.

Missing Values and Imputation

For most variables in the public data files, missing values are coded to identify the type of missing data.
These include

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•
•
•
•

(.L) Legitimate Skip – The item is not applicable to the respondent, as determined by a previous
answer to a root question.
(.M) Missing in Error – The value is missing due to respondent or system errors, or the
respondent did not provide a valid answer.
(.N) Not in Universe – The item was not included on the respondent’s age-appropriate version of
the topical questionnaire.
(.D) Suppressed for Confidentiality – The value is suppressed in order to protect respondent
confidentiality.

However, variables use for raking during weighting procedures require imputation. Table 15 lists the
2020 variables that are imputed and includes the imputation flag variables to indicate records with
imputed values. Tenure, sex, race, and Hispanic origin were imputed using hot-deck imputation. Adult 1
education, household size, and poverty ratio were imputed using sequential regression imputation
methods. 19
Table 15. Imputed Variables and Their Imputation Flags
Variable

Missing Rate

Imputation Flag Variable

Household tenure
(TENURE)

0.68%

Flag for Household Tenure
(TENURE_IF)

Child’s sex
(C_SEX)

0.18%

Flag for child’s sex
(C_SEX_IF)

Child’s race
(C_RACE_R)

0.81%

Flag for child’s race
(C_RACE_R_IF)

Child’s Hispanic origin
(C_HISPANIC_R)

0.59%

Flag for child’s Hispanic origin
(C_HISPANIC_R_IF)

Selected child’s sex
(SC_SEX)

0.08%

Flag for selected child’s sex
(SC_SEX_IF)

Selected child’s race
(SC_RACE_R)

0.47%

Flag for selected child’s race
(SC_RACE_R_IF)

Selected child’s Hispanic origin
(SC_HISPANIC_R)

0.36%

Flag for selected child’s Hispanic origin
(SC_HISPANIC_R_IF)

Adult 1’s highest completed
year of school
(A1_GRADE)

3.03%

Flag for adult 1’s highest completed
year of school
(A1_GRADE_IF)

Household size
(HHCOUNT)

2.80%

Flag for household size
(HHCOUNT_IF)

Family poverty ratio
(FPL)

19.69%

Flag for family poverty ratio
(FPL_IF)

For more information on data analysis using imputed values, see https://www2.census.gov/programssurveys/nsch/technical-documentation/methodology/NSCH-Analysis-with-Imputed-Data-Guide.pdf
19

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Multiple Imputation
Using sequential regression imputation methods, FPL is multiply imputed and contains six versions or
implicates. The public use file includes all six imputed values for FPL [FPL_I1-FPL_I6]. The primary
motivation for the multiple imputation is to allow interested researchers to appropriately account for
uncertainty in estimates using FPL that is hidden when using a single implicate. 20 FPL input includes
imputed values for family income (not included in the public use file) and number of people that are
family members (FAMCOUNT). An estimated family count (FAMCOUNT) was derived from HHCOUNT
and other household information when FAMCOUNT was not reported by the household. The imputation
was executed by sequential regression modeling imputation 21 using IVEWare. 22

Suppressed Variables

A number of variables had range caps or suppressed values to protect respondent confidentiality
consistent with U.S. Census Bureau protocols. For example, a reported value must represent at least
10,000 children (weighted estimate). These variables are listed in Table 16.
Table 16. Suppressed Variables
Variable

Description

Valid Values

TOTKIDS_R

Number of children living in the household

1=1
2=2
3=3
4 = 4+

MOMAGE

Age of mother when child was born

18 = 18 years or younger
45 = 45 years or older

K2Q35A_1_YEARS

Age of child when first diagnosed with
autism

1 = 1 year or younger
13 = 13 or 14 years old
15 = 15 years or older

BIRTHWT_OZ_S

Birth weight

72 = 72 oz. or less
155 = 155 oz. or more

K11Q43R

Number of time the child has moved to a
new address

13 = 13 or 14 times
15 = 15 or more times

A1_AGE

Age of Adult 1

75 = 75 years or older

A2_AGE

Age of Adult 2

75 = 75 years or older

A1_LIVEUSA

When Adult 1 came to live in the U.S.

1970 = Before or in 1970

A2_LIVEUSA

When Adult 2 came to live in the U.S.

1970 = Before or in 1970

BREASTFEDEND_DAY_S

Stopped breastfeeding, age in days

Suppressed if > 5

Schaefer JL, Graham JW. 2002. “Missing Data: Our View of State of the Art”. Psychological Methods, 7(2): 147-77.
Raghunathan TE, Lepkowski JM, Hoewyk JV, Solenberger PW. 2001. “A Multivariate Technique for Multiply
Imputing Missing Values using a Sequence of Regression Models”. Survey Methodology, 27: 85–95.
22
Raghunathan TE, Solenberger PW, Hoewyk JV. 2016. IVEware: Imputation and Variance Estimation Software
User’s Guide (Version 0.3). Ann Arbor, MI: Institute for Social Research, University of Michigan.
20
21

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Variable

Description

Valid Values

BREASTFEDEND_WK_S

Stopped breastfeeding, age in weeks

Suppressed if > 8

BREASTFEDEND_MO_S

Stopped breastfeeding, age in months

29 = 29 or more

FRSTFORMULA_DAY_S

First fed formula, age in days

Suppressed if > 6

FRSTFORMULA_WK_S

First fed formula, age in weeks

Suppressed if > 8

FRSTFORMULA_MO_S

First fed formula, age in months

12 = 12 or more

FRSTSOLIDS_DAY_S

First fed solids, age in days

Suppressed if > 1

FRSTSOLIDS_WK_S

First fed solids, age in weeks

Suppressed if > 4

FRSTSOLIDS_MO_S

First fed solids, age in months

15 = 15 or more

FPL

Family poverty ratio

50 = 50% or less
400 = 400% or more

FAMCOUNT

Family Count

8 = 8 or more

HHCOUNT

Household Count

10 = 10 or more

K4Q37

Received Special Services - Age in Years

16 = 16 or more

SESPLANYR

Special Education Plan - Age in Years

16 = 16 or more

SESPLANMO

Special Education Plan – Age in Months

Suppressed if SESPLANYR > 2

Geography Variables

The 2020 NSCH includes four geography variables on the Public Use File
•
•
•
•

FIPSST (State of Residence)
CBSAFP_YN (Core-Based Statistical Area Status)
METRO_YN (Metropolitan Statistical Area Status)
MPC_YN (Metropolitan Principal City Status)

Table 17 provides a general description of the geography variables and their valid values. To protect
respondent confidentiality, CBSAFP_YN, METRO_YN, and MPC_YN are not reported in some states. If a
variable or intersection of variables could be used to identify a geographic area within a state with a
child population under 100,000, reported values for that variable were replaced with ".D", indicating
"Suppressed for Confidentiality".
Table 17. List of Geography Variables
Variable
Description
Valid Values
FIPSST
State of Residence
[FIPS code]
CBSAFP_YN Core Based Statistical Area (CBSA): County or counties
.D = Suppressed for confidentiality
associated with at least one core (urbanized area or urban 1 = In a CBSA
cluster) of at least 10,000 population, plus adjacent
2 = Not in a CBSA
counties having a high degree of social and economic
integration with the core as measured through commuting
ties.
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Variable
METRO_YN

MPC_YN

Description
Metropolitan Statistical Area (MSA): County or counties
associated with at least one urbanized area of at least
50,000 population, plus adjacent counties having a high
degree of social and economic integration with the core as
measured through commuting ties.
Metropolitan Principal City: An incorporated place or
census designated place in a Metropolitan Statistical Area
that meets specific population and workforce
requirements.

Valid Values
.D = Suppressed for confidentiality
1 = In a MSA
2 = Not in a MSA
.D = Suppressed for confidentiality
1 = In a Metropolitan Principal City
2 = Not in a Metropolitan Principal
City

Additional geographies are identified through the intersection of CBSAFP_YN, METRO_YN, and MPC_YN
shown in Table 18.
Table 18. Geographies Identified at the Intersections
Intersection

Additional Geography Level

CBSAFP_YN =1 and
METRO_YN =2

Micropolitan Statistical Area: County or counties (or equivalent
entities) associated with at least one urban cluster of at least
10,000 but less than 50,000 population, plus adjacent counties
having a high degree of social and economic integration with the
core as measured through commuting ties

METRO_YN =1 and
MPC_YN=2

In an MSA, but not a Metropolitan Principal City: County or counties
associated with at least one urbanized area of at least 50,000
population, plus adjacent counties having a high degree of social
and economic integration with the core as measured through
commuting ties, but is not incorporated place or census designated
place within the Metropolitan Statistical Area.

Alternative and lower-level geographic identifiers are not included with the public use data file. Access
to these variables is restricted to the Federal Statistical Research Data Centers (RDCs). Researchers can
apply for RDC access; proposed projects must demonstrate scientific merit, require non-public data, be
feasible, pose no risk to respondent confidentiality, and provide benefit to Census Bureau programs. The
currently open RDCs are listed at https://www.census.gov/about/adrm/fsrdc/locations.html, and
additional information on the RDC application process is available at https://www.census.gov/programssurveys/ces/data/restricted-use-data/apply-for-access.html.

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Weighting Specifications
Overview
The NSCH uses child- and household-level weights for population-based estimates. These include
•
•
•

Final Weight for Screened-in Households (FWH)
Final Weight for Screener Children (FWS)
Final Weight for Interviewed Children (FWC)

Each weight is the product of the base sampling weight, nonresponse adjustment factors, and raking
adjustment (RAK). The FWC also includes a subsampling adjustment. Population controls are derived
from the 2019 American Community Survey (ACS).
For 2020, a change to the grouping process for the education dimension resulted in different state
groupings from previous years. Additionally, a ninth dimension, state by age group, was added to the
final raking process (RAK).
Base Weights (BW)
The weighting process began with the base sampling weight (BW) for each sample household. The base
weight (i.e., sampling interval) for each sample housing unit was the inverse of its probability of
selection for the screener. Base weights were calculated separately for each of the two strata and each
state, including the District of Columbia. If there had been no nonresponse and the survey frame was
complete, using this weight would give unbiased estimates for the survey population.
Screener Nonresponse Adjustment (SNA)
The Screener Nonrepsonse Adjustment (SNA) increases the weights of the households responding to the
Screener to account for all the households not responding to the Screener.
Households were categorized into sixteen groups to define the screener weight cells. Each cell was
based on each combination of stratum, webgroup (High Web or High Paper), metropolitan statistical
area status, and poverty indicator (the proportion of households with income less than 150% of the
federal poverty level at the block group level).
SNA was calculated using the following formula:
summed BW of screener interviews + count of screener non-interviews
�
�
summed BW of screener interviews

where the count of screener non-interviews is an estimate of the expected number of eligible
households (occupied, residential household) from those cases for which nothing is received back. The
expected number of eligible cases is estimated by taking the eligibility rate among the known cases and
applying it to the unknown cases.
The number of screener non-interviews was calculated using the following formula.

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�

summed BW of screener interviews
�
summed BW of screener interviews + summed BW of screener ineligible households
×

(summed BW of households with unknown screener eligibility)

The resulting SNA was assigned to every household in the cell.

Household-Level Post-Stratification Adjustment Factor (HPSA)
All households with children that completed a screener were given a household-level weight. In addition
to the base weight and screener nonresponse adjustment, a household post-stratification adjustment
was applied in order to achieve the final household screener weight. This factor consisted of ratio
adjustments to population controls at the household level obtained from the 2019 ACS data.
Households were put into one of 255 cells defined by state, race of the child selected for the topical, and
Hispanic origin (yes or no) of the selected child if the selected child’s race was White. Within each cell,
the household post-stratification adjustment was calculated as the ACS population count for the cell
divided by the cell’s weighted total. The product of the base weight, screener nonresponse adjustment,
and this household post-stratification adjustment constituted the final household screener weight.
First Raking to Population Controls: All Screener Children
All eligible children (four at most) from completed screener interviews were given a child-level screener
weight. The weights of children from completed screener interviews were adjusted to match the 2019
ACS estimates for the following characteristics:
•
•
•

Dimension #1 – State by Child’s Race (White alone, Black alone, Asian alone, Other)
Dimension #2 – State by Child’s Ethnicity (Hispanic, Non-Hispanic)
Dimension #3 – State by Child’s Sex by Child’s Age Group (0-5, 6-11, 12-17 years)

Each iteration of this process consisted of calculating three ratio adjustments, one for each dimension,
sequentially. The adjustment factor calculated for Dimension 1 was applied to the weights accordingly
and this newly adjusted weight went into the calculation of the adjustment factor for Dimension 2. This
iterative raking process continued until the difference between the sum of the weights and the control
total associated with each cell was less than 1% of the control. The resulting weight from this process
was the final child-level screener weight for each eligible child. Only the children selected for the topical
continued in the weighting process to eventually receive a final interviewed child weight.
Adjustment for Households with More than One Child
In households with multiple children, the selected child represented all eligible children in their
household. Thus, a within-household subsampling factor was applied to account for the selection of a
single child, as well as the oversampling for young children and children with special health care needs
(CSHCN). The value of this adjustment was the inverse of the probability of selection for the selected

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child. Probabilities varied by the number of children in the household, the presence of children aged 0-5,
and the presence of CSHCN.
Adjustment for Topical Nonresponse
Similar to the screener nonresponse adjustment, the weights of the households responding to the
topical needed to be increased to account for all of the households not responding to the topical. The
adjustment considered all topical interviews (complete and sufficient partial) defined by questionnaires
with valid answers for at least 25 of 50 test questions, and at least one item in Section H or beyond or the
respondent submitted the topical portion of the web instrument. Returned topical that did not meet the
criteria were considered a topical non-interview.
All topical-eligible households were put into one of sixteen cells depending on imputed poverty/non-poverty
status, web group (High Web vs. High Paper), tenure (owner occupied or not), and presence of CSHCN. The
topical nonresponse adjustment was calculated within each of the sixteen cells as:
weighted sum of topical interviews + weighted sum of topical non-interviews
�
�
weighted sum of topical interviews

After this adjustment, the selected children from topical non-interview households were no longer
involved in the weighting process and only interviewed children continued to the last steps.
Raking Adjustment
The final step of the weighting process is accomplished through iterative raking to population controls
attained from the ACS 2019 single-year estimates and the 2020 NSCH Screener data. The following nine
analytical domains of interest were used:
•
•
•
•
•
•
•
•
•

Dimension #1 – State by Household Poverty Ratio
Dimension #2 – State by Household Size
Dimension #3 – State Groupings by Respondent’s Education
Dimension #4 – State by Selected Child’s Race
Dimension #5 – State by Selected Child’s Ethnicity
Dimension #6 – State by Selected Child’s SHCN Status
Dimension #7 – State by Selected Child’s Age Group
Dimension #8 – National Selected Child’s Race by Ethnicity
Dimension #9 – National Selected Child’s Sex by Single Age

The iterative raking process uses at most 100 iterations or until the weights are stabilized. Weights are
stabilized when the absolute difference between the sum of the weights within each raking cell of all
nine dimensions and the control total associated with each raking cell is less than one percent of the
control.
For Dimension #3, some states needed to be grouped due to the low number of respondents in each
state with less than a high school degree. States were grouped with others that had similar education
distributions based on ACS data. The states were first sorted by the ACS-derived percent of children in
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households where the respondent has less than a high school degree, followed by an additional sort by
the percent of children in households where the respondent has a high school degree. State groupings
were made with the intent of keeping these distributions similar within each group. The result was 16
state groupings and 8 stand-alone states. The following were the resulting groupings:
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Group 1: Maine, New Hampshire, North Dakota, and Vermont
Group 2: Minnesota, Utah, and Virginia
Group 3: Hawaii, Iowa, Montana, and Wyoming
Group 4: Massachusetts and Colorado
Group 5: Connecticut, Nebraska, New Jersey, and South Dakota
Group 6: DC and Maryland
Group 7: Illinois, Oregon, and Rhode Island
Group 8: Michigan, Ohio, and Wisconsin
Group 9: Idaho, Kansas, and Washington
Group 10: Missouri and South Carolina
Group 11: Delaware, Kentucky, and Pennsylvania
Group 12: Alaska and West Virginia
Group 13: New York and North Carolina
Group 14: Alabama and Florida
Group 15: Arkansas and Louisiana
Group 16: Arizona and Texas
Stand-alone states: California, Georgia, Indiana, Mississippi, Nevada, New Mexico, Oklahoma,
and Tennessee

Trimming of Large Weights
The resulting weights from each iteration of the raking process were checked for extreme values to
prevent a small number of cases with large weights from having undue influence on estimates and
increasing the variance. An extreme value was determined to be a weight that exceeded the median
weight plus six times the interquartile range (IQR) of the weights in each state. These extreme weights
were truncated to this cutoff (median plus six times the IQR of weights in that state) and the weights
were checked for convergence to the controls. Convergence required the weighted total of each cell to
be within 1% of the control for the cell. If convergence was not met for every cell, another iteration of
the raking process was applied again. This process of raking and trimming was reiterated until
convergence was met and there were few extreme weights left. In general, the remaining extreme
weights were observed to be very close to the cutoff. The remaining extreme weights were truncated a
final time to the median plus six times the IQR in the state and the process was complete.

Population Controls
Population controls used throughout the weighting were derived from the 2019 ACS one-year estimates.
By using the 2019 ACS data, the weighted totals were ensured to match the most up-to-date population
control totals available for key demographic variables for children and households in the U.S. The
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controls were used in the household post-stratification adjustment, the raking to attain the child-level
screener weights, and the raking to attain the final topical interviewed children weights. Almost all
controls used were at the state level, except for the last two dimensions where national-level controls
were used in the second raking process.
For the household post-stratification adjustment, the NSCH household weights were adjusted so that
the sum of the weights equaled the 2019 ACS estimates for the number of households in each state by
race (White, Black, Asian, Other) and by Hispanic origin (yes or no) if the selected child’s race was White.
In the first raking process, up to four children from each screener received adjustments so that the sum
of the weights of all children listed on screeners equaled the ACS estimates for the number of children in
each state by race, state by Hispanic origin, and state by sex by age group (0-5, 6-11, 12-17 years).
Finally, in the second raking process, the weights of the NSCH topical interviewed children were
adjusted so that the sum of their weights equaled the ACS estimates for each state by family poverty
ratio (≤100%, 101-200%, >200%), household size ( ≤3, 4, >4), respondent’s highest level of education
(High School), race, Hispanic origin, and special health care needs status, as
well as race by ethnicity and sex by age in years at the national level.

Limitations
To minimize the variability of the weights caused by large adjustment factors, cells having fewer than 30
cases were collapsed with a neighboring cell. The adjustment factors were then calculated for the
merged cells by combining the population controls and the sample cases for the two cells. Since the
individual cells were combined, and only one adjustment factor was created per cell, only the weighted
total for the combined cell will match the control following the raking procedure. Consequently, the
weighted totals for the individual cells will most likely not match the population controls for the original
individual cells. As shown in Table 19, cells were collapsed in two of the dimensions in the last raking
step.
Table 19. Collapsed Dimensions of Final Raking and Affected States
Collapse

Dimension Collapsed

Affected States

Black collapsed with
Other in 26 states

Dimension #4 - State by Selected Child’s AK, AZ, CA, CO, CT, HI, ID, IA, KS, ME, MA, MN,
Race (White, Black, Asian, Other)
MT, NE, NH, NM, ND, OK, OR, SD, UT, VT, WA,
WV, WI, WY

Asian collapsed with
Other in 35 states

Dimension #4 - State by Selected Child’s AL, AZ, AR, CO, DC, FL, ID, IN, IA, KS, KY, LA, ME,
Race (White, Black, Asian, Other)
MI, MS, MO, MT, NE, NH, NM, NC, ND, OH, OK,
OR, PA, RI, SC, SD, TN, UT, VT, WV, WI, WY

Hispanic and NonDimension #5 - State by Selected Child’s AL, KY, ME, MI, MS, MO, ND, SD, VT, WV
Hispanic collapsed in 10 Ethnicity (Hispanic, Non-Hispanic)
states

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Estimation, Hypothesis Testing, and Data Use Guidelines
Variance Estimation

When survey weights are used, the resulting estimates from the 2020 NSCH are representative of all
non-institutionalized children aged 0 to 17 years in the U.S. and in each state and the District of
Columbia who live in housing units. These weighted estimates do not generalize to the population of
parents, mothers, or pediatric health care providers. Analysts are advised to avoid statements such as
“the percent of parents”.
Two stratum identifiers should be used to estimate variance: FIPSST (state of residence) and STRATUM
(identifies households flagged with children). Each record in the data file is assigned a unique household
identifier, HHID. Some analysts may be using statistical programs that only permit the specification of a
single stratum variable. These users should define a new variable with 102 levels by crossing STRATUM (2
levels) with FIPSST (51 levels). This new variable can then be used as the stratum variable. For example,
Stata users can specify only one variable in the strata() option of svyset. This new variable (named here
as STRATACROSS) can be created using the following statement:
•

EGEN STRATACROSS = GROUP (FIPSST STRATUM)

SUDAAN users can identify both FIPSST and STRATUM in the NEST statement. However, SUDAAN users
should note that the first variable listed after the word NEST is assumed to be the stratum variable, and
the second variable listed is assumed to be the PSU. To properly identify the PSU variable, the PSULEV
option must be invoked in the NEST statement as shown here:
•

NEST FIPSST STRATUM HHID / PSULEV = 3;

In both individual year and multi-year analyses, the NSCH sample size may be limited for smaller
populations (e.g., American Indian or Alaska Native) and state-level subgroups or rare outcomes (e.g.,
adolescent CSHCN or autism in a particular state). Small sample sizes may produce unstable
estimates. To minimize misinterpretation, we recommend only presenting statistics with a sample
size or unweighted denominator of 30 or more. Further, if the 95% confidence interval width exceeds
20 percentage points or 1.2 times the estimate (≈ relative standard error >30%), we recommend
flagging for poor reliability and/or presenting a measure of statistical reliability (e.g., confidence
intervals or statistical significance testing) to promote appropriate interpretation.
State-level estimates may be compared to national estimates using a nested z-test to identify
significant differences at a given alpha or Type 1 error level (e.g., 0.05, 0.01). The formula for this is as
follows:
𝑍𝑍 =

2020 National Survey of Children’s Health

𝑋𝑋�𝑖𝑖 − 𝑋𝑋�𝑗𝑗

�𝑆𝑆𝐸𝐸𝑖𝑖2 + 𝑆𝑆𝐸𝐸𝑗𝑗2 − 2𝑃𝑃 ∗ 𝑆𝑆𝐸𝐸𝑗𝑗2
U.S. Census Bureau

48

Where j is a subset of i (e.g., Alabama as part of the Total US), 𝑋𝑋� is the mean or proportion, SE is the
standard error, and P is the proportion of the weighted denominator for a given indicator that is
specific to j (e.g., Alabama weighted denominator divided by the Total US weighted denominator). A
simple independent Z-test would be a more conservative test that may increase Type II error—the
probability of failing to reject the null of no difference when there is a difference.

Combining Data across Survey Years

Data across multiple years of the redesigned NSCH (2016 and later) can be combined to increase the
analytic sample size. By leveraging a larger sample, data users can analyze smaller population groups
and rare outcomes that are not sufficiently represented in a single year sample and produce national
and state-level estimates with smaller standard errors. Guidance for producing multi-year estimates is
available at https://www2.census.gov/programs-surveys/nsch/technicaldocumentation/methodology/NSCH-Guide-to-Multi-Year-Estimates.pdf.

Confidentiality

Participation in the 2020 NSCH was voluntary, and all data collected that could potentially identify an
individual person are confidential. Data are kept private in accordance with applicable law. Respondents
are assured of the confidentiality of their replies in accordance with 13 U.S.C. Section 9. All access to
Title 13 data from this survey is restricted to Census Bureau employees and those holding Census
Bureau Special Sworn Status pursuant to 13 U.S.C. Section 23(c). In compliance with this law, all data
released to the public are only in a statistical format. No information that could personally identify a
respondent or household may be released. The Screener and Topical public use data files went through
a thorough disclosure review process and were approved by the Census Disclosure Review Board prior
to release.

Guidelines for Data Use

The U.S. Census Bureau is conducting the NSCH on the behalf of the Health Resources and Services
Administration’s Maternal and Child Health Bureau (HRSA MCHB) within the U.S. Department of Health
and Human Services (HHS) under Title 13, United States Code, Section 8(b), which allows the Census
Bureau to conduct surveys on behalf of other agencies. Title 42 U.S.C. Section 701(a)(2) allows HHS to
collect information for the purpose of understanding the health and well-being of children in the U.S.
The data collected under this agreement are confidential under 13 U.S.C. Section 9. All access to Title 13
data from this survey is restricted to Census Bureau employees and those holding Census Bureau Special
Sworn Status pursuant to 13 U.S.C. Section 23(c).
Any effort to determine the identity of any reported case is prohibited. The Census Bureau and HRSA
MCHB take extraordinary measures to assure that the identity of survey subjects cannot be disclosed. All
direct identifiers, as well as characteristics that might lead to identification, have been omitted from the
data set. Any intentional identification or disclosure of a person or establishment violates the assurances
of confidentiality given to the providers of the information. Therefore, users must:
•

Use the data in this data set for statistical reporting and analysis only

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•
•

Make no use of the identity of any person discovered, inadvertently or otherwise
Not link this data set with individually identifiable data from any other Census Bureau or nonCensus Bureau data sets

Use of the data set signifies users’ agreement to comply with the previously stated statutory-based
requirements. Before releasing any statistics to the public, the Census Bureau reviews them to make
sure none of the information or characteristics could identify someone. For more information about the
Census Bureau’s privacy and confidentiality protections, contact the Policy Coordination Office toll-free
at 1-800-923-8282.

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Supporting Material
References
Bethell CD, Read D, Neff J, Blumberg SJ, Stein RE, Sharp V, Newacheck PW. 2002. “Comparison of the
Children with Special Health Care Needs Screener to the Questionnaire for Identifying Children with
Chronic Conditions—Revised.” Ambulatory Pediatrics, Jan-Feb 2(1): 49-57.
Blumberg SJ, Luke JV. 2010. Wireless Substitution: Early Release of Estimates from the National Health
Interview Survey, January–June 2010. National Center for Health Statistics. Available from:
http://www.cdc.gov/nchs/nhis.htm
Blumberg SJ, Foster EB, Frasier AM, et al. 2012. Design and Operation of the National Survey of
Children’s Health, 2007. National Center for Health Statistics. Vital Health Stat, 1(55). Available from:
http://www.cdc.gov/nchs/data/series/sr_01/sr01_055.pdf
Bramlett MD, Blumberg SJ, Ormson AE, et al. 2014. Design and Operation of the National Survey of
Children with Special Health Care Needs, 2009–2010. National Center for Health Statistics. Vital Health
Stat, 1(57). Available from: http://www.cdc.gov/nchs/data/series/sr_01/sr01_057.pdf
Brick JM, Williams D, Montaquila JM. 2011. “Address-Based Sampling for Subpopulation Surveys.” Public
Opinion Quarterly, 75(3): 409-28.
Dillman DA, Smyth JD, Christian LM. 2009. Internet, Mail and Mixed-Mode Surveys: The Tailored Design
Method, 3rd edition. Hoboken, NJ: John Wiley & Sons.
Foster EB, Frasier AM, Morrison HM, O’Connor KS, Blumberg SJ. 2010. All Things Incentive: Exploring the
Best Combination of Incentive Conditions. Paper presented at the American Association for Public
Opinion Research annual conference, Chicago, IL.
Raghunathan TE, Lepkowski JM, Hoewyk JV, Solenberger PW. 2001. “A Multivariate Technique for
Multiply Imputing Missing Values using a Sequence of Regression Models.” Survey Methodology, 27: 8595.
Raghunathan TE, Solenberger PW, Hoewyk JV. 2016. IVEware: Imputation and Variance Estimation
Software User’s Guide (Version 0.3). Ann Arbor, MI: Institute for Social Research, University of Michigan.
Schaefer JL, Graham JW. 2002. “Missing Data: Our View of State of the Art”. Psychological Methods,
7(2): 147-77.

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Attachment A: 2020 Estimated State-Level Sample Sizes
State sample sizes by stratum were determined using the following criteria. First, the Stratum 1
oversampling rates for each state were maximized such that the variance did not far exceed that of a
design that sampled equally in the two strata. Second, the target number of topical interviews per state
was adjusted until the total sample size was at the desired size. For 2020, approximately 240,000
addresses yielded 700 topical interviews per state and 960 topical interviews per oversampled state.
Table A-1: Address Sample Size and Strata Distribution by State
State
Total Sample
Stratum 1 Stratum 2A
(approx.)
Alabama
5000
60.9%
39.1%
Alaska
5800
51.1%
48.9%
Arizona
4900
56.6%
43.4%
Arkansas
5200
61.4%
38.6%
California
4000
68.7%
31.3%
Colorado
9400
58.4%
41.6%
Connecticut
3600
64.6%
35.4%
Delaware
4400
67.8%
32.2%
DC
4500
63.7%
36.3%
Florida
5100
59.5%
40.5%
Georgia
5000
61.7%
38.3%
Hawaii
6100
31.2%
68.8%
Idaho
3400
58.7%
41.3%
Illinois
3900
62.5%
37.5%
Indiana
4000
61.8%
38.2%
Iowa
3300
64.7%
35.3%
Kansas
3600
62.8%
37.2%
Kentucky
4600
60.9%
39.1%
Louisiana
6100
59.7%
40.3%
Maine
4300
59.2%
40.8%
Maryland
3500
65.9%
34.1%
Massachusetts
3200
67.3%
32.7%
Michigan
3300
69.5%
30.5%
Minnesota
2500
69.7%
30.3%
Mississippi
5900
61.8%
38.2%
Missouri
3800
65.3%
34.7%
Montana
4900
51.8%
48.2%
Nebraska
5200
63.7%
36.3%
Nevada
5000
60.1%
39.9%
New Hampshire
3600
63.9%
36.1%
New Jersey
3600
65.3%
34.7%
20

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New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming

2020 National Survey of Children’s Health

6100
4900
4400
3900
3900
5200
14500
3300
4200
4700
4000
4300
5100
2800
3900
3400
3600
5200
7000
5000

49.1%
56.5%
59.6%
60.9%
61.9%
56.7%
64.8%
67.9%
61.8%
65.7%
57.4%
62.4%
62.6%
69.7%
59.0%
64.6%
62.2%
52.5%
68.6%
53.3%

50.9%
43.5%
40.4%
39.1%
38.1%
43.3%
35.2%
32.1%
38.2%
34.3%
42.6%
37.6%
37.4%
30.3%
41.0%
35.4%
37.8%
47.5%
31.4%
46.7%

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Attachment B: Probabilities for Selected Child
Respondents are given a household type (1, 2, 3A, 3B, 4, 5A, 5B, 5C, 6, 7, 8) based on the following
variables from screener responses:
•
•
•
•
•

TOTKIDS_E Total number of eligible children
CHILDY0_5 Indicator child in 0-5 years old
CHILDN0_5 Indicator child is not 0-5 years old
TOTCSHCN Total number of special needs children
TOTNON Total number of not special needs children

Each household type has rules of probability to select a child for the topical questionnaire. Some
household types include an oversample for child selection based on age and special needs. Table B-1
shows each household type, their corresponding combination of variable, and a child’s probability of
selection from that household.
Table B-1: Household Type Assignment from the Values of Five Screener Variables
Household
Variables
Type
TOTKIDS_E CHILDY0_5 CHILDN0_5 TOTCSHCN TOTNON
Probability of
Selection
TYPE=1
0 or blank
No Child
→
n/a
n/a
n/a
n/a
HHTYP_1
TYPE=2
1
n/a
n/a
n/a
n/a
100% (Single Child)
→
HHTYP_2
TYPE=3A
2
2
0
2
0
50%
→
0
2
HHTYP_3A
0
2
2
0
0
2
TYPE=3B
2
1
1
2
0
0-5 years old: 62%
→
6-17 years old: 38%
0
2
HHTYP_3B
TYPE=4
2
n/a
n/a
1
1
CSHCN: 64%
→
non-CSHCN: 36%
HHTYP_4
TYPE=5A
3
3
0
3
0
33%
→
0
3
HHTYP_5A
0
3
3
0
0
3
TYPE=5B
3
1
2
3
0
0-5 years old: 44%
→
6-17 years old: 28%
0
3
HHTYP_5B
TYPE=5C
3
2
1
3
0
0-5 years old: 38%
→
6-17
years old: 24%
0
3
HHTYP_5C
21

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TYPE=6
→
HHTYP_6
TYPE=7
→
HHTYP_7
TYPE=8
→
HHTYP_8

3

n/a

n/a

1

2

CSHCN: 48%
non-CSHCN: 26%

3

n/a

n/a

2

1

CSHCN: 39%
non-CSHCN: 22%

≥4

n/a

n/a

n/a

2020 National Survey of Children’s Health

n/a

25%

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Attachment C: Envelope Design Options
Standard Business Envelope Traditional

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Standard Business Envelope Redesign (Front/Back)

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Flat Mail Envelope Traditional (Front/Back)

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Flat Mail Envelope Redesign (Front/Back)

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USPS Priority Mail Envelope (Front/Back)

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Attachment D: Weighted Response Rates by State
Table D-1. Weighted Response Rates by State

22

State
United States
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
District of Columbia
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts

Resolution
Rate
52.2%
52.4%
64.5%
55.5%
54.9%
48.3%
56.3%
51.5%
47.6%
52.9%
48.1%
47.3%
65.2%
60.1%
52.4%
53.3%
60.8%
55.6%
57.4%
49.7%
63.5%
50.7%
54.6%

Screener
Conversion
Rate
99.1%
99.0%
99.6%
99.0%
99.3%
98.4%
99.2%
98.9%
99.1%
99.4%
99.5%
99.3%
99.5%
99.3%
98.6%
99.1%
99.7%
99.2%
99.4%
98.8%
99.7%
98.9%
98.8%

Screener
Completion
Rate
47.1%
46.4%
53.8%
48.9%
46.6%
44.5%
50.6%
47.9%
43.4%
49.2%
42.9%
41.8%
59.9%
53.8%
48.0%
48.7%
57.4%
49.6%
51.7%
41.4%
53.9%
47.3%
51.1%

2020 National Survey of Children’s Health

Topical
Conversion
Rate
82.0%
79.5%
77.5%
78.3%
77.7%
77.4%
82.0%
78.2%
79.1%
85.0%
79.9%
79.9%
75.6%
83.3%
77.3%
79.3%
83.2%
82.7%
79.8%
77.3%
78.7%
81.0%
81.8%

Topical
Completion
Rate
36.4%
36.0%
37.5%
35.8%
32.8%
33.7%
39.2%
38.1%
32.7%
44.0%
34.0%
32.3%
46.0%
42.3%
37.5%
38.8%
40.9%
40.4%
36.8%
31.4%
36.0%
39.3%
42.6%

Interview
Completion
Rate
81.2%
78.7%
77.2%
77.5%
77.1%
76.1%
81.3%
77.3%
78.4%
84.5%
79.4%
79.3%
75.2%
82.7%
76.2%
78.6%
83.0%
82.1%
79.4%
76.4%
78.4%
80.1%
80.9%

Overall
Response
Rate
42.4%
41.2%
49.8%
43.0%
42.3%
36.8%
45.8%
39.8%
37.3%
44.7%
38.2%
37.5%
49.0%
49.7%
39.9%
41.9%
50.4%
45.6%
45.5%
38.0%
49.8%
40.6%
44.1%

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Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming

52.2%
60.5%
49.6%
57.2%
67.9%
61.2%
46.7%
59.2%
48.5%
59.0%
47.8%
47.9%
64.9%
52.5%
57.1%
58.4%
54.6%
46.7%
51.4%
64.5%
51.1%
47.0%
58.4%
69.8%
54.0%
57.1%
62.6%
58.6%
65.8%

99.1%
98.8%
98.9%
99.2%
99.9%
99.4%
99.5%
99.5%
99.2%
99.5%
99.0%
98.9%
99.6%
99.1%
99.7%
99.2%
99.5%
99.1%
99.2%
99.5%
98.9%
98.8%
98.8%
99.5%
98.7%
99.5%
99.7%
98.9%
99.7%

2020 National Survey of Children’s Health

47.3%
56.2%
41.8%
51.1%
62.1%
57.4%
42.2%
52.5%
45.3%
51.7%
43.6%
42.2%
59.4%
47.8%
51.0%
54.6%
49.0%
43.1%
46.0%
59.8%
45.9%
40.7%
53.9%
62.1%
50.2%
53.6%
54.8%
54.5%
57.0%

81.5%
82.5%
74.9%
82.4%
85.4%
84.1%
81.5%
83.5%
79.3%
76.4%
78.4%
80.1%
83.6%
82.0%
78.6%
83.7%
80.4%
79.6%
82.5%
80.6%
79.9%
79.0%
86.1%
83.2%
79.9%
82.3%
77.4%
82.5%
82.6%

37.7%
44.0%
30.6%
40.8%
46.1%
42.1%
33.3%
40.3%
38.8%
33.9%
35.0%
33.3%
44.8%
37.0%
34.9%
43.3%
36.3%
32.5%
37.9%
41.1%
33.9%
31.7%
44.6%
47.2%
39.5%
41.7%
35.0%
42.7%
40.1%

80.7%
81.5%
74.1%
81.7%
85.3%
83.6%
81.0%
83.1%
78.6%
76.0%
77.7%
79.2%
83.2%
81.3%
78.4%
83.0%
80.0%
78.8%
81.8%
80.2%
79.0%
78.0%
85.0%
82.7%
78.9%
81.9%
77.1%
81.6%
82.4%

U.S. Census Bureau

42.1%
49.3%
36.7%
46.7%
58.0%
51.1%
37.9%
49.2%
38.2%
44.9%
37.1%
37.9%
54.0%
42.6%
44.8%
48.5%
43.7%
36.8%
42.0%
51.7%
40.4%
36.7%
49.6%
57.8%
42.6%
46.8%
48.2%
47.8%
54.2%
62