MEPS HC-189: 2016 Food Security
July 2018
Agency for Healthcare Research and Quality
Center for Financing, Access, and Cost Trends
5600 Fishers Lane
Rockville, MD 20857
(301) 427-1406
Table of Contents
A. Data Use Agreement
B. Background
1.0 Household Component
2.0 Medical Provider Component
3.0 Survey Management and Data Collection
C. Technical and Programming Information
1.0 General Information
2.0 Data File Information
2.1 Codebook Structure
2.2 Reserved Codes
2.3 Codebook Format
2.4 Variable Naming
2.5 File Contents
2.5.1 Survey Administration Variables (HOMEIDX – PANEL)
2.5.2 Food Security Variables (FSOUT42 – FSNEDY42)
2.6 Linking to Other Files
2.6.1 MEPS Public Use Files
2.6.2 National Health Interview Survey
2.6.3 Longitudinal Analysis
3.0 Survey Sample Information
3.1 Background on Sample Design and Response Rates
3.1.1 References
3.1.2 MEPS-Linked to the National Health Interview Survey (NHIS)
3.1.3 Sample Weights and Variance Estimation
3.2 The MEPS Sampling Process and Response Rates: An Overview
3.2.1 Response Rates
3.2.2 Panel 21 Response Rates
3.2.3 Panel 20 Response Rates
3.2.4 Annual (Combined Panel) Response Rate
3.2.5 Oversampling
3.3 Food Security Weight (FSWT42)
3.4 Variance Estimation
3.4.1 Taylor-series Linearization Method
3.4.2 Balanced Repeated Replication (BRR) Method
D. Variable-Source Crosswalk
Individual identifiers have been removed from the
micro-data contained in these files. Nevertheless, under sections 308 (d) and
903 (c) of the Public Health Service Act (42 U.S.C. 242m and 42 U.S.C. 299 a-1),
data collected by the Agency for Healthcare Research and Quality (AHRQ) and/or
the National Center for Health Statistics (NCHS) may not be used for any purpose
other than for the purpose for which they were supplied; any effort to determine
the identity of any reported cases is prohibited by law.
Therefore in accordance with the above referenced
Federal Statute, it is understood that:
- No one is to use the data in this data set in any way except
for statistical reporting and analysis; and
- If the identity of any person or establishment should be
discovered inadvertently, then (a) no use will be made of this
knowledge, (b) the Director Office of Management AHRQ will be
advised of this incident, (c) the information that would
identify any individual or establishment will be safeguarded or
destroyed, as requested by AHRQ, and (d) no one else will be
informed of the discovered identity; and
- No one will attempt to link this data set with individually
identifiable records from any data sets other than the Medical
Expenditure Panel Survey or the National Health Interview
Survey. Furthermore, linkage of the Medical Expenditure Panel
Survey and the National Health Interview Survey may not occur
outside the AHRQ Data Center, NCHS Research Data Center (RDC) or
the U.S. Census RDC network.
By using these data you signify your agreement to
comply with the above stated statutorily based requirements with the knowledge
that deliberately making a false statement in any matter within the jurisdiction
of any department or agency of the Federal Government violates Title 18 part 1
Chapter 47 Section 1001 and is punishable by a fine of up to $10,000 or up to 5
years in prison.
The Agency for Healthcare Research and Quality
requests that users cite AHRQ and the Medical Expenditure Panel Survey as the
data source in any publications or research based upon these data.
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The Medical Expenditure Panel Survey (MEPS) provides
nationally representative estimates of health care use, expenditures, sources of
payment, and health insurance coverage for the U.S. civilian
noninstitutionalized population. The MEPS Household Component (HC) also provides
estimates of respondents’ health status, demographic and socio-economic
characteristics, employment, access to care, and satisfaction with health care.
Estimates can be produced for individuals, families, and selected population
subgroups. The panel design of the survey, which includes 5 Rounds of interviews
covering 2 full calendar years, provides data for examining person level changes
in selected variables such as expenditures, health insurance coverage, and
health status. Using computer assisted personal interviewing (CAPI) technology,
information about each household member is collected, and the survey builds on
this information from interview to interview. All data for a sampled household
are reported by a single household respondent.
The MEPS-HC was initiated in 1996. Each year a new
panel of sample households is selected. Because the data collected are
comparable to those from earlier medical expenditure surveys conducted in 1977
and 1987, it is possible to analyze long-term trends. Each annual MEPS-HC sample
size is about 15,000 households. Data can be analyzed at either the person or
event level. Data must be weighted to produce national
estimates.
The set of households selected for each panel of the
MEPS HC is a subsample of households participating in the previous year’s
National Health Interview Survey (NHIS) conducted by the National Center for
Health Statistics. The NHIS sampling frame provides a nationally representative
sample of the U.S. civilian noninstitutionalized population and reflects an
oversample of Blacks and Hispanics. In 2006, the NHIS implemented a new sample
design, which included Asian persons in addition to households with Black and
Hispanic persons in the oversampling of minority populations. The linkage of the
MEPS to the previous year’s NHIS provides additional data for longitudinal
analytic purposes.
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Upon completion of the household CAPI interview and
obtaining permission from the household survey respondents, a sample of medical
providers are contacted by telephone to obtain information that household
respondents can not accurately provide. This part of the MEPS is called the
Medical Provider Component (MPC) and information is collected on dates of
visits, diagnosis and procedure codes, charges and payments. The Pharmacy
Component (PC), a subcomponent of the MPC, does not collect charges or diagnosis
and procedure codes but does collect drug detail information, including National
Drug Code (NDC) and medicine name, as well as date filled and sources and
amounts of payment. The MPC is not designed to yield national estimates. It is
primarily used as an imputation source to supplement/replace household reported
expenditure information.
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MEPS HC and MPC data are collected under the authority
of the Public Health Service Act. Data are collected under contract with Westat,
Inc. (MEPS HC) and Research Triangle Institute (MEPS MPC). Data sets and summary
statistics are edited and published in accordance with the confidentiality
provisions of the Public Health Service Act and the Privacy Act. The National
Center for Health Statistics (NCHS) provides consultation and technical
assistance.
As soon as data collection and editing are completed,
the MEPS survey data are released to the public in staged releases of summary
reports, micro data files, and tables via the
MEPS website. Selected data can be
analyzed through MEPSnet, an on-line interactive tool designed to give data
users the capability to statistically analyze MEPS data in a menu-driven
environment.
Additional information on MEPS is available from the
MEPS project manager or the MEPS public use data manager at the Center for
Financing, Access, and Cost Trends, Agency for Healthcare Research and Quality,
5600 Fishers Lane, Rockville, MD 20857 (301-427-1406).
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This documentation describes the 2016 food security
data file from the Medical Expenditure Panel Survey Household Component (MEPS
HC). Released as an ASCII file (with related SAS, SPSS, and Stata programming
statements and data user information) and a SAS transport dataset, this public
use file provides information collected on a nationally representative sample of
the civilian noninstitutionalized population of the United States for calendar
year 2016. The file contains 16 variables and has a logical record length of 51
with an additional 2-byte carriage return/line feed at the end of each record.
This file consists of MEPS survey data obtained in
Round 4 of Panel 20 and Round 2 of Panel 21, in calendar year 2016, and contains
variables pertaining to food security.
The following documentation offers a brief overview of
the types and levels of data provided, content and structure of the files, and
programming information. It contains the following sections:
- Data File Information
- Survey Sample Information
- Variable-Source Crosswalk
Both weighted and unweighted frequencies of most
variables included in the 2016 food security data file are provided in the
accompanying codebook file. The exceptions to this are weight variables and
variance estimation variables. Only unweighted frequencies of these variables
are included in the accompanying codebook file. See the Weights Variables list
in Section D, Variable-Source Crosswalk.
A database of all MEPS products released to date and a
variable locator indicating the major MEPS data items on public use files that
have been released to date can be found at the following link on the
MEPS website.
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This public use dataset contains variables and
frequency distributions associated with 13,500 households who
participated in the MEPS Household Component of the Medical Expenditure Panel
Survey in 2016. These households received a positive family-level weight and
were part of one of the two MEPS panels for whom food security data were
collected in Round 4 of Panel 20 or Round 2 of Panel 21.
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The codebook and data file sequence lists variables in
the following order:
- Unique household identifiers and survey administration
variables
- Food security variables
- Weight and variance estimation variables
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The following reserved code values are used:
| Value |
Definition |
| -1 INAPPLICABLE |
Question was not asked due to skip pattern |
| -7 REFUSED |
Question was asked and respondent refused to answer question |
| -8 DK |
Question was asked and respondent did not know answer |
| -9 NOT ASCERTAINED |
Interviewer did not record the data |
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This codebook describes an ASCII data set and provides the following programming identifiers for each variable:
| Identifier |
Description |
| Name |
Variable name (maximum of 8 characters) |
| Description |
Variable descriptor (maximum 40 characters) |
| Format |
Number of bytes |
| Type |
Type of data: numeric (indicated by NUM) or character (indicated by CHAR) |
| Start |
Beginning column position of variable in record |
| End |
Ending column position of variable in record |
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Variable names reflect the content of the variable,
with an eight-character limitation. The last two characters denote the rounds of
data collection, Round 4 of Panel 20 and Round 2 of Panel 21.
Variables contained in this delivery were derived
either from the questionnaire itself or from the CAPI. The source of each
variable is identified in Appendix 1 “Variable-Source Crosswalk.” Sources for
each variable are indicated in one of three ways: (1) variables derived from
CAPI or assigned in sampling are so indicated; (2) variables collected at one or
more specific questions have those numbers and questionnaire sections indicated
in the “SOURCE” column; and (3) variables constructed from multiple questions
using complex algorithms are labeled “Constructed” in the “SOURCE” column.
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HOMEIDX uniquely identifies each household on the file
and consists of the Dwelling Unit ID (DUID) followed by the RU letter and round
number.
The definitions of Dwelling Units (DUs) in the MEPS
Household Survey are generally consistent with the definitions employed for the
National Health Interview Survey (NHIS). The DUID is a five-digit random ID
number assigned after the case was sampled for MEPS.
PANEL is a constructed variable used to specify the
panel number for the person. PANEL will indicate either Panel 20 or Panel 21 for
each person on the file. Panel 20 is the panel that started in 2015, and Panel
21 is the panel that started in 2016.
Households are eligible for the Food Security PUF if
the MEPS interview was completed by an RU member and if the household is not a
student RU.
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Respondents were asked:
Variable |
Description |
| FSOUT42 – |
how often in the last 30 days anyone in the household worried whether food would run
out before getting money to buy more |
| FSLAST42 – |
how often in the last 30 the food purchased didn’t last and the person/household
didn’t have money to get more |
| FSAFRD42 – |
how often in the last 30 the person/household could not afford to eat balanced meals |
| FSSKIP42 – |
in the last 30 days did the person/household reduce or skip meals because there wasn’t
enough money for food (coded as “-1 Inapplicable” when FSOUT42, FSLAST42, and FSAFRD42 = 3, -7, -8, or -9) |
| FSSKDY42 – |
how many meals were skipped in the last 30 days (coded as “-1 Inapplicable”
when FSSKIP42 = 2, -7, -8, or -9 OR when FSOUT42, FSLAST42, and FSAFRD42 = 3, -7, -8, or -9) |
| FSLESS42 – |
in the last 30 days did the person/household ever eat less because there wasn’t
enough money for food (coded as “-1 Inapplicable” when FSOUT42, FSLAST42, and FSAFRD42 = 3, -7, -8, or -9) |
| FSHGRY42 – |
in the last 30 days was the person/household ever hungry but didn’t eat because
there wasn’t enough money for food (coded as “-1 Inapplicable” when FSOUT42, FSLAST42, and
FSAFRD42 = 3, -7, -8, or -9) |
| FSWTLS42 – |
in the last 30 days did anyone in the household lose weight because there wasn’t
enough money for food (coded as “-1 Inapplicable” when FSOUT42, FSLAST42, and FSAFRD42 = 3, -7, -8, or -9) |
| FSNEAT42 – |
in the last 30 days did anyone in the household not eat for a whole day because there
wasn’t enough money for food (coded as “-1 Inapplicable” when FSOUT42, FSLAST42, and
FSAFRD42 = 3, -7, -8, or -9; or when FSLESS42, FSHGRY42, and FSWTLS42 = 2, -7, -8, or -9) |
| FSNEDY42 – |
how many days in the last 30 days anyone in the household had not eaten for a whole day
because there wasn’t enough money for food (coded as “-1 Inapplicable” when FSOUT42, FSLAST42, and
FSAFRD42 = 3, -7, -8, or -9; or when FSLESS42, FSHGRY42, and FSWTLS42 = 2, -7, -8, or -9; or when
FSNEAT42 = 2, -7, -8, or -9) |
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The family (RU) level records in this public use file
can be linked to the 2016 full year Consolidated file to obtain additional data
for the families included in this file. To link the records with the
Consolidated data file records, create an RU ID using the first six characters
of HOMEIDX (columns 1-5 are DUID and column 6 is RU letter). On the full year
Consolidated file concatenate DUID with RULETR42 (Round 4/2 RU letter) to obtain
an equivalent ID. The records in both files can then be linked with this ID. The
reference person of the RU can be identified in the Consolidated data file by
the variable REFPRS42.
Food Security PUF:
Includes HOMEIDX(12345A4) as DUID(12345) + RULETER42(A) + Round(4)
Construct RUID(12345A) as substr(HOMEIDX, 1,6)
Consolidated PUF: Includes DUID(12345) and RULETER42(A)
Construct RUID(12345A) as DUID(12345) + RULETER42(A)
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The set of households selected for MEPS is a subsample
of those participating in the National Health Interview Survey (NHIS), thus,
each MEPS panel can also be linked back to the previous year’s NHIS public use
data files. For information on obtaining MEPS/NHIS link files please see the
AHRQ website.
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Panel-specific longitudinal files are available for
downloading in the data section of the MEPS website. For each panel, the
longitudinal file comprises MEPS survey data obtained in Rounds 1 through 5 of
the panel and can be used to analyze changes over a two-year period. Variables
in the file pertaining to survey administration, demographics, employment,
health status, disability days, quality of care, patient satisfaction, health
insurance, and medical care use and expenditures were obtained from the MEPS
full-year Consolidated files from the two years covered by that panel.
For more details or to download the data files, please
see Longitudinal Weight Files at the
AHRQ website.
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The MEPS is designed to produce estimates at the
national and regional level over time for the civilian, noninstitutionalized
population of the United States and some subpopulations of interest. The MEPS
data in this public use file pertain to calendar year 2016. The data were
collected in Rounds 1, 2, and 3 for MEPS Panel 21 and Rounds 3, 4, and 5 for
MEPS Panel 20. (Note that Round 3 for a MEPS panel is designed to overlap two
calendar years, as illustrated below.) The 2016 food security data were
collected only in Round 4 of Panel 20 and Round 2 of Panel 21.
A sample design feature shared by both Panel 20 and
Panel 21 involved the partitioning of the sample domain “Other” (serving as the
catchall stratum, and consisting mainly of households with “White” members) into
two sample domains. This was done for the first time in Panel 16. The two
domains were defined as: those households characterized as “complete” respondents to the NHIS; and those characterized as “partial completes.” NHIS “partial completes” typically have a lower response rate to MEPS and for both
MEPS panels the “partial” domain was sampled at a lower rate than the “complete” domain. This approach served to reduce survey costs, since the “partials” tend
to have higher costs in gaining survey participation, but increased sample
variability due to the resulting increased variance in sampling rates.
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There have been some published reports on the MEPS
sample design. For detailed information on the MEPS sample design, see Cohen,
S., Sample Design of the 1997 Medical Expenditure Panel Survey Household
Component. Rockville (MD): Agency for Healthcare Research and Quality; 2000.
MEPS Methodology Report, No. 11. AHRQ Pub. No. 01-0001 and Ezzati-Rice, T.M.,
Rohde, F., Greenblatt, J., (2008).
Sample Design of the Medical
Expenditure Panel Survey Household Component, 1998-2007, Methodology Report, No.
22. March 2008. Agency for Healthcare
Research and Quality, Rockville, MD.
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Each responding household found in this 2016 MEPS
dataset is associated with one of two separate and overlapping MEPS panels, MEPS
Panel 20 and MEPS Panel 21. These panels consist of subsamples of households
participating in the 2014 and 2015 NHIS, respectively, and reflecting the NHIS
sample design first implemented in 2006.
Whenever there is a change in sample or study design,
it is good survey practice to assess whether such a change could affect the
sample estimates. For example, increased coverage of the target populations with
an updated sample design based on data from the latest Census can improve the
accuracy of the sample estimates. MEPS estimates have been and will continue to
be evaluated to determine if an important change in the survey estimates might
be associated with a change in design. It may be noted that 2016 is the last
year for which both MEPS panels reflect the 2006 NHIS sample design. MEPS Panel
22 (fielded in 2017) will reflect the new NHIS design, first implemented in
2016. To the extent that users compare MEPS estimates to 2016 NHIS estimates,
they should be cognizant of this design change as it may affect the extent to
which MEPS and NHIS data are comparable. An overview of the new
CDC NHIS sample design can be found at the CDC website.
As background, the NHIS is a complex multi-stage
sample design. A brief and simplified description of the NHIS design follows.
The first stage of sample selection is an area sample of PSUs, where PSUs
generally consist of one or more counties. Within PSUs, density strata are
formed, generally reflecting the density of minority populations for single or
groups of blocks or block equivalents that are assigned to the strata. Within
each such density stratum “supersegments” are formed, consisting of clusters of
housing units. Samples of supersegments are selected for use over a 10-year data
collection period for the NHIS. Households within supersegments are selected for
each calendar year the NHIS is carried out. In the NHIS sample design used since
2006, Asians are oversampled in addition to Hispanics and Blacks. These features
of the NHIS complex survey design carry over to the MEPS. The only major
difference in eligibility status for housing units between NHIS and MEPS is that
college dorms represent ineligible housing units for MEPS. College aged students
living away from home during the school year were interviewed at their place of
residence for the NHIS but were identified by and linked to their parents’
household for MEPS. (There is also a person-level stage of sampling for the NHIS,
but that does not affect the MEPS sample design.)
The households (occupied DUs) selected for MEPS Panel
20 were a subsample of the 2014 NHIS responding households, while those in MEPS
Panel 21 were a subsample of 2015 NHIS responding households. A MEPS household
may contain one or more family units, each consisting of one or more
individuals. Analysis using MEPS data can be undertaken using either the
individual or the family as the unit of analysis.
There were 10,610 households (occupied DUs) selected
for MEPS Panel 20, of which 10,571 were eligible for fielding (college
dormitories were eliminated). They were randomly selected from among the
households responding to the 2014 NHIS. A subsample of 9,700 households was
randomly selected for MEPS Panel 21 from the households responding to the 2015
NHIS, of which 9,658 were fielded for MEPS after the elimination of college
dorms.
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In the dataset MEPS HC-189: 2016 Food Security Data
File, a weight variable is provided for generating MEPS estimates of totals,
means, percentages, and rates for families in the civilian noninstitutionalized
population. Procedures and considerations associated with the construction and
interpretation of family estimates using these and other variables are discussed
below.
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For most MEPS panels, a sample representing about
three-eighths of the NHIS responding households is made available for use in
MEPS. This was the case for both MEPS Panel 20 and Panel 21.
Because the MEPS subsampling has to be done soon after
NHIS responding households are identified, a small percentage of the NHIS
households initially characterized as NHIS respondents are later classified as
nonrespondents for the purposes of NHIS data analysis. This actually serves to
increase the overall MEPS response rate slightly since the percentage of NHIS
households designated for use in MEPS (all those characterized initially as
respondents from the NHIS panels and quarters used by MEPS for a given year) is
slightly larger than the final NHIS household-level response rate and some NHIS
nonresponding households do participate in MEPS. However, as a result, these
NHIS nonrespondents who are MEPS participants have no NHIS data available to
link with MEPS data. Once the MEPS sample is selected from among the NHIS
households characterized as NHIS respondents, RUs representing students living
in student housing or consisting entirely of military personnel are deleted from
the sample. For the NHIS, college students living in student housing are sampled
independently from their families. For MEPS, such students are identified
through the sample selection of their parents’ RU. Removing from MEPS those
college students found in college housing sampled for the NHIS eliminates the
opportunity of multiple chances of selection for MEPS for these students.
Military personnel not living in the same RU as civilians are ineligible for
MEPS. After such exclusions, all RUs associated with households selected from
among those identified as NHIS responding households are then fielded in the
first round of MEPS.
Table 3.1 shows in Rows A, B, and C the three
informational components just discussed. Row A indicates the percentage of NHIS
households eligible for MEPS. Row B indicates the number of NHIS households
sampled for MEPS. Row C indicates the number of sampled households actually
fielded for MEPS (after dropping the students and military members discussed
above). Note that all response rates discussed here are unweighted.
Table 3.1. Sample Size and Unweighted Response Rates for 2016 Full Year File (Panel 21 Rounds 1-3/Panel 20, Rounds 3-5)
Sample Size |
Panel 20 |
Panel 21 |
2016 Combined |
| A. Percentage of NHIS households designated for use in MEPS (those initially characterized as responding) * |
75.1% |
71.2% |
— |
| B. Number of households sampled from the NHIS |
10,610 |
9,700 |
— |
| C. Number of Households sampled from the NHIS and fielded for MEPS |
10,571 |
9,658 |
— |
| D. Round 1 – Number of RUs eligible for interviewing |
11,283 |
10,280 |
— |
| E. Round 1 – Number of RUs with completed interviews |
8,287 |
7,643 |
— |
| F. Round 2 – Number of RUs eligible for interviewing |
8,554 |
7,870 |
— |
| G. Round 2 – Number of RUs with completed interviews |
7,991 |
7,319 |
— |
| H. Round 3 – Number of RUs eligible for interviewing |
8,136 |
7,478 |
— |
| I. Round 3 – Number of RUs with completed interviews |
7,743 |
7,035 |
— |
| J. Round 4 – Number of RUs eligible for interviewing |
7,877 |
— |
— |
| K. Round 4 – Number of RUs with completed interviews |
7,621 |
— |
— |
| L. Round 5 – Number of RUs eligible for interviewing |
7,698 |
— |
— |
| M. Round 5 – Number of RUs with completed interviews |
7,421 |
— |
— |
Overall annual unweighted response rates
P21: A x (E/D) x (G/F) x (I/H)
P20: A x (E/D) x (G/F) x (I/H) x (K/J) x (M/L)
Combined: 0.510 x P20 + 0.490 x P21 |
45.7% (Panel 20 through Round 5) |
46.3% (Panel 21 through Round 3) |
46.0% |
*Among the panels and quarters of the NHIS allocated to MEPS, the percentage of households that were considered to be NHIS respondents at the time the MEPS sample was selected.
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In order to produce annual health care estimates for
calendar year 2016 based on the full MEPS sample data from the MEPS Panel 20 and
Panel 21, the two panels are combined. More specifically, full calendar year
2016 data collected in Rounds 3 through 5 for the MEPS Panel 20 sample are
pooled with data from the first three rounds of data collection for the MEPS
Panel 21 sample (the general approach is described below).
As mentioned above, all response rates discussed here
are unweighted. To understand the calculation of MEPS response rates, some
features related to MEPS data collection should be noted. When an RU is visited
for a round of data collection, changes in RU membership are identified. Such
changes include the formation of student RUs as well as other new RUs created
when RU members from a previous round have moved to another location in the U.S.
Thus, the number of RUs eligible for MEPS interviewing in a given round is
determined after data collection is fully completed. The ratio of the number of
RUs completing the MEPS interview in a given round to the number of RUs
characterized as eligible to complete the interview for that round represents
the “conditional” response rate for that round expressed as a proportion. It is “conditional” in that it pertains to the set of RUs characterized as eligible
for MEPS for that round and thus is “conditioned” on prior participation rather
than representing the overall response rate through that round. For example, in
Table 3.1, for Panel 21 Round 2 the ratio of 7,319 (Row G) to 7,870 (Row F)
multiplied by 100 represents the response rate for the round (93.0 percent when
computed), conditioned on the set of RUs characterized as eligible for MEPS for
that round. Taking the product of the percentage of the NHIS sample eligible for
MEPS (Row A) with the product of the ratios for a consecutive set of MEPS rounds
beginning with Round 1 produces the overall response rate through the last MEPS
round specified.
The overall unweighted response rate for the combined
sample of Panel 20 and Panel 21 for 2016 was obtained by computing the products
of the relative sample sizes and the corresponding overall panel response rates
and then summing the two products. Panel 21 represents about 49.0 percent of the
combined sample size while Panel 20 represents the remaining 51.0 percent. Thus,
the combined response rate of 46.0 percent was computed as 0.510 times 45.7, the
overall Panel 20 response rate through Round 5 plus 0.490 times 46.3, the
overall Panel 21 response rate through Round 3.
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For MEPS Panel 21 Round 1, 9,658 households were
fielded in 2016 (Row C of Table 3.1), a randomly selected subsample of the
households responding to the 2015 National Health Interview Survey (NHIS).
Table 3.1 shows the number of RUs eligible for
interviewing in each Round of Panel 21 as well as the number of RUs completing
the MEPS interview. Computing the individual round “conditional” response rates
as described in section 3.2.1 and then taking the product of these three
response rates and the factor 71.2 (the percentage of the NHIS sampled
households designated for use in selecting a sample of households for MEPS)
yields an overall response rate of 46.3 percent for Panel 21 through Round 3.
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For MEPS Panel 20, 10,571 households were fielded in
2015 (as indicated in Row C of Table 3.1), a randomly selected subsample of the
households responding to the 2014 National Health Interview Survey (NHIS).
Table 3.1 shows the number of RUs eligible for
interviewing and the number completing the interview for all five rounds of
Panel 20. The overall response rate for Panel 20 was computed in a similar
fashion to that of Panel 21 but covering all five rounds of MEPS interviewing as
well the factor representing the percentage of NHIS sampled households eligible
for MEPS. The overall response rate for Panel 20 through Round 5 is 45.7
percent.
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A combined panel response rate for the survey
respondents in this data set is obtained by taking a weighted average of the
panel specific response rates. The Panel 20 response rate was weighted by a
factor of 0.510 and Panel 21 was weighted by a factor of 0.490, reflecting
approximately the distribution of the overall sample between the two panels. The
resulting combined response rate for the combined panels was computed as (0.510
x 45.7) plus (0.490 x 46.3) or 46.0 percent (as shown in Table 3.1).
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Oversampling is a feature of the MEPS sample design,
helping to increase the precision of estimates for some subgroups of interest.
Before going into details related to MEPS, the concept of oversampling will be
discussed.
In a sample where all persons in a population are
selected with the same probability and survey coverage of the population is
high, the sample distribution is expected to be proportionate to the population
distribution. For example, if Hispanics represent 15 percent of the general
population, one would expect roughly 15 percent of the persons sampled to be
Hispanic. However, in order to improve the precision of estimates for specific
subgroups of a population, one might decide to select samples from those
subgroups at higher rates than the remainder of the population. Thus, one might
select Hispanics at twice the rate (i.e., at double the probability) of persons
not oversampled. As a result, an oversampled subgroup comprises a higher
proportion of the sample than it represents in the general population. Sample
weights ensure that population estimates are not distorted by a disproportionate
contribution from oversampled subgroups. Base sample weights for oversampled
groups will be smaller than for the portion of the population not oversampled.
For example, if a subgroup is sampled at roughly twice the rate of sample
selection for the remainder of the population not oversampled, members of the
oversampled subgroup will receive base or initial sample weights (prior to
nonresponse or poststratification adjustments) that are roughly half the size of
the group not oversampled.
As mentioned above, oversampling is implemented to
increase the sample sizes and thus improve the precision of survey estimates for
particular subgroups of the population. The “cost” of oversampling is that the
precision of estimates for the general population and subgroups not oversampled
will be reduced to some extent compared to the precision one could have achieved
if the same overall sample size were selected without any oversampling.
The oversampling of Hispanic, Black, and Asian
households for the NHIS carries over to MEPS through the set of NHIS responding
households eligible for sample selection for MEPS. In the NHIS under the old
sample design utilized through 2005, Hispanic households were oversampled at a
rate of roughly 2 to 1. That is, the probability of selecting a Hispanic
household for participation in the NHIS was roughly twice that for households in
the general population that were not oversampled. The oversampling rate for
Black households under the old design was roughly 1.5 to 1. Under the NHIS
sample design employed through 2015 (which is the sample design applicable for
MEPS Panels 20 and 21), Asians, as well as Hispanics and Blacks, are
oversampled. The average oversampling rates for the three minority groups have
not yet been reported.
For both Panel 20 and Panel 21, all households in the
Asian, Hispanic, and Black domains were sampled with certainty (i.e., all
households assigned to those domains were included in the MEPS). For Panel 20,
the “Other, complete” domain was sampled at a rate of about 84 percent while the “Other, partial complete” domain was sampled at a rate of about 53 percent. For
Panel 21, the corresponding sampling rates for the “Other, complete” domain and
the “Other, partial complete” domain were about 81 percent and 49 percent,
respectively.
Within strata (domains) for both panels, responding
NHIS households were selected for MEPS using a systematic sample selection
procedure from among those eligible. For the “non-Other” strata households were
all selected with certainty. Within strata involving “Others” (two strata for
both panels) the selection was with probability proportionate to size (pps)
where the size measure was the inverse of the NHIS initial probability of
selection. The pps sampling was undertaken to help reduce the variability in the
MEPS weights incurred due to the variability of the NHIS sampling rates. With
the subsampling, households that were oversampled for MEPS in calendar year 2016
were those responding households in the NHIS identified as having members whose
race/ethnicity was Hispanic, Black, or Asian for both panels.
Typically, sample allocations across sample domains
change from one MEPS panel to another. The sample domains used may also vary by
panel although this was not the case for Panel 20 and Panel 21. When one
compares unweighted measures (e.g., response rates) between panels and years,
one should take into account such differences. If, for example, members of one
domain have a lower propensity to respond than those of another domain, then if
that domain has been allocated a higher proportion of the sample, the
corresponding panel may have a lower unweighted response rate simply because of
the differences in sample allocation.
Within each domain (sample stratum) systematic samples
of the MEPS-eligible households were selected from among the NHIS household
respondents made available for MEPS sample selection purposes.
Return To Table Of Contents
The Food Security questionnaire was administered to RU
level respondents in Round 4 of Panel 20 and Round 2 of Panel 21. A family
weight specific to Rounds 4/2, FSWT42, was created for the purposes of analyzing
the Food Security questionnaire data. To create FSWT42, first those RUs that
were MEPS respondents in Round 4/2, were identified. The MEPS family weight (FAMWT16F)
from the 2016 full year Consolidated data file of the RU reference person was
then assigned as the family weight of the RU. A small number of RUs (less than 2
percent) had a reference person with no MEPS family weight in the Consolidated
data file because at least one member of the family became a nonrespondent for
MEPS in the subsequent round. For these RUs, the reference person’s full-year
person weight was assigned as the family weight. The reference person of the RU
in MEPS is defined as the household member 16 years of age or older who own or
rents the home. Note that there are two different family weights provided in the
2016 Full Year Consolidated PUF: the MEPS family weight, FAMWT16F; and the
family weight based on the Current Population Survey (CPS) definition of a
family, FAMWT16C. The MEPS family weight (FAMWT16F) was used for the food
security data because the MEPS family weight definition of family was closest to
the MEPS Round 4/2 RU definition. For more information on the derivation of
FAMWT16F and FAMWT16C, see the MEPS HC-192, 2016 Full Year Consolidated Data
File Documentation. Table 3.2 shows the number of families in the food security
data file by panel and the weighted total number of the families.
Table 3.2. Numbers of families by Panel and the
weighted total number of families
Number |
Panel 20 |
Panel 21 |
Combined |
Population estimate
(weighted total of combined sample) |
| Number |
6,946 |
6,554 |
13,500 |
137,402,160 |
Return To Table Of Contents
The MEPS is based on a complex sample design. To
obtain estimates of variability (such as the standard error of sample estimates
or corresponding confidence intervals) for MEPS estimates, analysts need to take
into account the complex sample design of MEPS for both person-level and
family-level analyses. Several methodologies have been developed for estimating
standard errors for surveys with a complex sample design, including the
Taylor-series linearization method, balanced repeated replication, and jackknife
replication. Various software packages provide analysts with the capability of
implementing these methodologies. MEPS analysts most commonly use the Taylor
Series approach. However, an option is also provided to apply the BRR approach
when needed to develop variances for more complex estimators.
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The variables needed to calculate appropriate standard
errors based on the Taylor-series linearization method are included on this and
all other MEPS public use files. Software packages that permit the use of the
Taylor-series linearization method include SUDAAN, Stata, SAS (version 8.2 and
higher), and SPSS (version 12.0 and higher). For complete information on the
capabilities of each package, analysts should refer to the corresponding
software user documentation.
Using the Taylor-series linearization method, variance
estimation strata and the variance estimation PSUs within these strata must be
specified. The variables VARSTR and VARPSU on this MEPS data file serve to
identify the sampling strata and primary sampling units required by the variance
estimation programs. Specifying a “with replacement” design in one of the
previously mentioned computer software packages will provide estimated standard
errors appropriate for assessing the variability of MEPS survey estimates. It
should be noted that the number of degrees of freedom associated with estimates
of variability indicated by such a package may not appropriately reflect the
number available. For variables of interest distributed throughout the country
(and thus the MEPS sample PSUs), one can generally expect to have at least 100
degrees of freedom associated with the estimated standard errors for national
estimates based on this MEPS database.
Prior to 2002, MEPS variance strata and PSUs were
developed independently from year to year, and the last two characters of the
strata and PSU variable names denoted the year. However, beginning with the 2002
Point-in-Time PUF, the variance strata and PSUs were developed to be compatible
with all future PUFs until the NHIS design changed. Thus, when pooling data
across years 2002 through the Panel 11 component of the 2007 files, the variance
strata and PSU variables provided can be used without modification for variance
estimation purposes for estimates covering multiple years of data. There were
203 variance estimation strata, each stratum with either two or three variance
estimation PSUs.
From Panel 12 of the 2007 files, a new set of variance
strata and PSUs were developed because of the introduction of a new NHIS design.
There are 165 variance strata with either two or three variance estimation PSUs
per stratum starting from Panel 12. Therefore, there are a total of 368
(203+165) variance strata in the 2007 Full Year file as it consists of two
panels that were selected under two independent NHIS sample designs. Since both
MEPS panels in the Full Year 2008 file and beyond are based on the new NHIS
design, there are only 165 variance strata. These variance strata (VARSTR
values) have been numbered from 1001 to 1165 so that they can be readily
distinguished from those developed under the former NHIS sample design in the
event that data are pooled for several years.
To ensure that variance strata are identified
appropriately for variance estimation purposes when pooling MEPS data across
several years, one can proceed as follows:
- When pooling any year from 2002 or later, one can use the
variance strata numbering as is.
- When pooling any year from 1996 to 2001 with any year from
2002 or later, use the pooled linkage public use file HC-036
that contains the proper variance structure to use when making
estimates from MEPS data that have been pooled over multiple
years and where one or more years are from 1996-2001.
- The HC-036 file is updated every year to allow pooling of
any year from 1996 to 2001 with any year from 2002 up to the
latest year. Further details on the HC-036 file can be found in
the public use documentation of the HC-036 file.
Return To Table Of Contents
BRR replicate weights are not provided on this MEPS
PUF for the purposes of variance estimation. However, a file containing a BRR
replication structure is made available so that the users can form replicate
weights, if desired, from the final MEPS weight to compute variances of MEPS
estimates using either BRR or Fay’s modified BRR (Fay 1989) methods. The
replicate weights are useful to compute variances of complex non-linear
estimators for which a Taylor linear form is not easy to derive and not
available in commonly used software. For instance, it is not possible to
calculate the variances of a median or the ratio of two medians using the Taylor
linearization method. For these types of estimators, users may calculate a
variance using BRR or Fay’s modified BRR methods. However, it should be noted
that the replicate weights have been derived from the final weight through a
shortcut approach. Specifically, the replicate weights are not computed starting
with the base weight and all adjustments made in different stages of weighting
are not applied independently in each replicate. So the variances computed using
this one-step BRR do not capture the effects of all weighting adjustments that
would be captured in a set of full developed BRR replicate weights. The Taylor
Series approach does not fully capture the effects of the different weighting
adjustments either.
The dataset HC-036BRR contains the information
necessary to construct the BRR replicates. It contains a set of 128 flags
(BRR1—BRR128) in the form of half sample indicators, each of which is coded 0 or
1 to indicate whether the person should or should not be included in that
particular replicate. These flags can be used in conjunction with the full-year
weight to construct the BRR replicate weights. For analysis of MEPS data pooled
across years, the BRR replicates can be formed in the same way using the HC-036
file. For more information about creating BRR replicates, users can refer to the
documentation for the HC-036BRR pooled linkage file.
Return To Table Of Contents
VARIABLE-SOURCE CROSSWALK
FOR MEPS HC-189: 2016 FOOD SECURITY DATA FILE
SURVEY ADMINISTRATION VARIABLES
| VARIABLE |
DESCRIPTION |
SOURCE |
| HOMEIDX |
HOME ID NUMBER (DUID + RU + ROUND) |
Constructed |
| DUID |
DWELLING UNIT ID |
Assigned in Sampling |
| PANEL |
PANEL |
Constructed |
Return To Table Of Contents
FOOD SECURITY VARIABLES – PUBLIC USE
| VARIABLE |
DESCRIPTION |
SOURCE |
| FSOUT42 |
HOW OFTEN HAVE YOU RUN OUT OF FOOD |
FS02 |
| FSLAST42 |
HOW OFTEN DID FOOD NOT LAST |
FS03 |
| FSAFRD42 |
HOW OFTEN NOT AFFORD BALANCED MEALS |
FS04 |
| FSSKIP42 |
DID YOU EVER SKIP MEALS |
FS05 |
| FSSKDY42 |
HOW MANY DAYS WERE MEALS SKIPPED |
FS06 |
| FSLESS42 |
DID YOU EVER EAT LESS |
FS07 |
| FSHGRY42 |
DID YOU EVER GO HUNGRY |
FS08 |
| FSWTLS42 |
LOW FOOD MONEY CAUSE WEIGHT LOSS |
FS09 |
| FSNEAT42 |
DID YOU EVER NOT EAT |
FS10 |
| FSNEDY42 |
HOW MANY DAYS DID YOU NOT EAT |
FS11 |
Return To Table Of Contents
WEIGHTS VARIABLES – PUBLIC USE
| VARIABLE |
DESCRIPTION |
SOURCE |
| FSWT42 |
FOOD SECURITY WEIGHT |
Constructed |
| VARSTR |
VARIANCE ESTIMATION STRATUM - 2016 |
Constructed |
| VARPSU |
VARIANCE ESTIMATION PSU - 2016 |
Constructed |
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|
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