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Updated: Jul 6, 2026

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
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Published on: May 10, 2019

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

Carolyn A Liebler1, Andrew Halpern-Manners

  • 1Department of Sociology and Minnesota Population Center, University of Minnesota, 55455, USA. liebler@umn.edu

Demography
|April 9, 2008
PubMed
Summary
This summary is machine-generated.

New federal policies allow multiple race responses, but data analysis is challenging. This study offers a practical regression method to incorporate multiple-race individuals into analyses using public-use microdata.

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Last Updated: Jul 6, 2026

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06:55

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Published on: January 8, 2020

Area of Science:

  • Sociology
  • Demography
  • Public Health

Background:

  • Revised federal policies mandate the inclusion of multiple-race responses in data collection.
  • Researchers face significant challenges in utilizing the complexity of multiple-race data for analysis.
  • Comparability issues hinder the use of multiple-race data across different datasets and time periods.

Purpose of the Study:

  • To present a practical method for incorporating multiple-race respondents into analyses using public-use microdata.
  • To adapt and apply existing regression methods for analyzing multiple-race data.
  • To provide a user-friendly tool for researchers to include multiple-race individuals in their studies.

Main Methods:

  • Modification of the National Center for Health Statistics (NCHS) regression method.
  • Utilizing specific race combinations and individual/contextual characteristics to predict preferred single race.
  • Application of NCHS-generated regression coefficients to public-use microdata with limited geographic information.

Main Results:

  • Successful application of the modified regression method to public-use microdata.
  • Development of a downloadable computer program to facilitate the method's use.
  • Demonstration of a practical approach for including multiple-race respondents in analyses.

Conclusions:

  • The proposed method offers a practical and preferable solution for analyzing multiple-race data.
  • This approach addresses the challenges researchers face with new federal race data policies.
  • The downloadable program enhances the accessibility and utility of multiple-race data in research.