A practical approach to using multiple-race response data: A bridging method for public-use microdata

Carolyn A. Liebler, Andrew Halpern-Manners

Research output: Contribution to journalArticlepeer-review

53 Scopus citations

Abstract

Revised federal policies require that multiple-race responses be allowed in all federal data collection efforts, but many researchers find the multitude of race categories and variables very difficult to use. Important comparability issues also interfere with using multiple-race data in analyses of multiple data sets and/or several points in time. These difficulties have, in effect, discouraged the use of the new data on race. We present a practical method for incorporating multiple-race respondents into analyses that use public-use microdata. Our method is a modification of the regression method developed by the National Center for Health Statistics (NCHS), which uses multiple-race respondents' specific combination of races, as well as other individual-level and contextual characteristics, to predict the respondents 'preferred single race. In this paper we (1) apply the NCHS-generated regression coefficients to public-use microdata with limited geographic information; and (2) provide a downloadable computer program with which researchers can apply this practical and preferable method for including multiple-race respondents in a wide variety of analyses.

Original languageEnglish (US)
Pages (from-to)143-155
Number of pages13
JournalDemography
Volume45
Issue number1
DOIs
StatePublished - Feb 2008

Bibliographical note

Funding Information:
The first author began this project while she was funded by “IPUMS-Redesign” (NIH GRANT R01-HD043392), Steven Ruggles, Principle Investigator. We presented a draft of this work at the 2007 annual meetings of the Population Association of America, New York. We thank J. Trent Alexander, Douglas Hartmann, Elaine M. Hernandez, Deborah D. Ingram, C. Matthew Snipp, and John Robert Warren for their helpful feedback, and the Minnesota Population Center for its invaluable research support.

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