From single-race reporting to multiple-race reporting: using imputation methods to bridge the transition
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Updated: Sep 26, 2026

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
Published on: May 10, 2019
Nathaniel Schenker1, Jennifer D Parker
1Office of Research and Methodology, National Center for Health Statistics, Hyattsville, MD 20782, USA. nschenker@cdc.gov
Abstract:
In 1997, the Office of Management and Budget issued revised standards for the collection of race information within the Federal statistical system. One revision allows individuals to choose more than one race group when responding to Federal surveys and other Federal data collections. This paper explores methods that impute single-race categories for those who have given multiple-race responses. Such imputations would be useful when it is desired to conduct analyses involving only single-race categories, such as when trends over time are being examined by race group so that data collected under the old and new standards are being combined. The National Health Interview Survey has allowed multiple-race responses for several years, while also asking respondents to specify one race as their primary race. Exploratory analyses of data from the survey suggest that imputation methods that use demographic and contextual covariate information to predict primary race can have advantages with respect to lower bias and improved variance estimation compared to simpler methods discussed by the Office of Management and Budget. It also appears, however, that the relationships between primary race and covariates might be changing over time. Thus, caution should be exercised if an imputation model fitted to data from one time period is to be applied to data from another time period. Published in 2003 by John Wiley & Sons, Ltd.
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