<i>CATAcode</i> : A Principled Approach for Coding Check-All-That-Apply Demographic Items

Accurately measuring, reporting, interpreting, and evaluating identity categories in social-science research is essential; however, check-all-that-apply (CATA) responses present methodological challenges because of the large permutations of categories and the fluctuating salience of intersecting identities across time and contexts. These challenges can hinder the validity of quantitative studies, particularly those examining racial, ethnic, and other social-identity differences. Although quantitative-critical-race-theory scholars have proposed principles for handling racial and ethnic categories in quantitative research, their application in statistical analyses remains limited. In this article, we introduce CATAcode , an R package designed to assist researchers in exploring and preparing CATA demographic items for statistical modeling. By applying this tool to cross-sectional and longitudinal data, in the tutorial, we demonstrate how CATAcode can enhance the generalizability, transparency, and reproducibility of social-science research. Improving the rigor of demographic measurement is essential for identifying and addressing social inequalities, allocating resources, and understanding broader patterns of marginalization.