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Making the Most of Multiple Measures: Disentangling the Effects of Different Dimensions of Race in Survey Research

Saperstein, Aliya, Jessica M. Kizer, and Andrew M. Penner. 2016. "Making the Most of Multiple Measures: Disentangling the Effects of Different Dimensions of Race in Survey Research." American Behavioral Scientist60(4):519-537.

The majority of social science research uses a single measure of race when investigating racial inequality. However, a growing body of work demonstrates that race shapes the life chances of individuals in multiple ways, related not only to how people self-identify but also to how others perceive them. As multiple measures of race are increasingly collected and used in survey research, it becomes important to consider the best methods of leveraging such data. We present four analytical approaches for incorporating two different dimensions of race in the same study and illustrate their use with data from the U.S. National Longitudinal Study of Adolescent to Adult Health. The approaches range from tests of specific hypotheses to the most exploratory description of how different measures of race relate to social inequality. Although each approach has its strengths and weaknesses, by accounting for the multidimensionality of race, they all allow for more nuanced patterns of advantage and disadvantage than standard single-measure methods.

American Behavorial Scientist
2016
Jessica M. Kizer
Andrew M. Penner