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 datasets and/or multiple points in time. These difficulties have, in effect, discouraged the use of the more nuanced new data on race. We present a practical method for incorporating multiple-race respondents into analyses that use public-use Microdata. We extend prior work by the National Center for Health Statistics (NCHS) in which they use multiple-race respondents preferred single race and other characteristics to develop a model predicting preferred single race (if forced to choose). In this paper, we apply the NCHS-generated regression coefficients to public-use Microdata with limited geographic information. We include documentation and dissemination tools for this practical and preferable method of including multiple-race respondents in analyses.
|Original language||English (US)|
|State||Published - 2007|