Bridging a Survey Redesign Using Multiple Imputation: An Application to the 2014 CPS ASEC

The Current Population Survey Annual Social and Economic Supplement (CPS ASEC) serves as the data source for official income, poverty, and inequality statistics in the United States. In 2014, the CPS ASEC questionnaire was redesigned to improve data quality and to reduce misreporting, item nonrespon...

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Main Author: Rothbaum Jonathan
Format: Article
Language:English
Published: Sciendo 2017-03-01
Series:Journal of Official Statistics
Subjects:
Online Access:https://doi.org/10.1515/jos-2017-0010
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spelling doaj-b252f28406654bf59396aca3963173042021-09-06T19:40:52ZengSciendoJournal of Official Statistics2001-73672017-03-0133118720610.1515/jos-2017-0010jos-2017-0010Bridging a Survey Redesign Using Multiple Imputation: An Application to the 2014 CPS ASECRothbaum Jonathan0Social and Economic Housing Statistics Division, U.S. Census Bureau, 4600 Silver Hill Road, Washington, DC 20233, United States of AmericaThe Current Population Survey Annual Social and Economic Supplement (CPS ASEC) serves as the data source for official income, poverty, and inequality statistics in the United States. In 2014, the CPS ASEC questionnaire was redesigned to improve data quality and to reduce misreporting, item nonresponse, and errors resulting from respondent fatigue. The sample was split into two groups, with nearly 70% receiving the traditional instrument and 30% receiving the redesigned instrument. Due to the relatively small redesign sample, analyses of changes in income and poverty between this and future years may lack sufficient power, especially for subgroups. The traditional sample is treated as if the responses were missing for income sources targeted by the redesign, and multiple imputation is used to generate plausible responses. A flexible imputation technique is used to place individuals into strata along two dimensions: 1) their probability of income recipiency and 2) their expected income conditional on recipiency for each income source. By matching on these two dimensions, this approach combines the ideas of propensity score matching and predictive means matching. In this article, this approach is implemented, the matching models are evaluated using diagnostics, and the results are analyzed.https://doi.org/10.1515/jos-2017-0010multiple imputationsurvey redesignbridgecps asec
collection DOAJ
language English
format Article
sources DOAJ
author Rothbaum Jonathan
spellingShingle Rothbaum Jonathan
Bridging a Survey Redesign Using Multiple Imputation: An Application to the 2014 CPS ASEC
Journal of Official Statistics
multiple imputation
survey redesign
bridge
cps asec
author_facet Rothbaum Jonathan
author_sort Rothbaum Jonathan
title Bridging a Survey Redesign Using Multiple Imputation: An Application to the 2014 CPS ASEC
title_short Bridging a Survey Redesign Using Multiple Imputation: An Application to the 2014 CPS ASEC
title_full Bridging a Survey Redesign Using Multiple Imputation: An Application to the 2014 CPS ASEC
title_fullStr Bridging a Survey Redesign Using Multiple Imputation: An Application to the 2014 CPS ASEC
title_full_unstemmed Bridging a Survey Redesign Using Multiple Imputation: An Application to the 2014 CPS ASEC
title_sort bridging a survey redesign using multiple imputation: an application to the 2014 cps asec
publisher Sciendo
series Journal of Official Statistics
issn 2001-7367
publishDate 2017-03-01
description The Current Population Survey Annual Social and Economic Supplement (CPS ASEC) serves as the data source for official income, poverty, and inequality statistics in the United States. In 2014, the CPS ASEC questionnaire was redesigned to improve data quality and to reduce misreporting, item nonresponse, and errors resulting from respondent fatigue. The sample was split into two groups, with nearly 70% receiving the traditional instrument and 30% receiving the redesigned instrument. Due to the relatively small redesign sample, analyses of changes in income and poverty between this and future years may lack sufficient power, especially for subgroups. The traditional sample is treated as if the responses were missing for income sources targeted by the redesign, and multiple imputation is used to generate plausible responses. A flexible imputation technique is used to place individuals into strata along two dimensions: 1) their probability of income recipiency and 2) their expected income conditional on recipiency for each income source. By matching on these two dimensions, this approach combines the ideas of propensity score matching and predictive means matching. In this article, this approach is implemented, the matching models are evaluated using diagnostics, and the results are analyzed.
topic multiple imputation
survey redesign
bridge
cps asec
url https://doi.org/10.1515/jos-2017-0010
work_keys_str_mv AT rothbaumjonathan bridgingasurveyredesignusingmultipleimputationanapplicationtothe2014cpsasec
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