Non-white, no more: Effect coding as an alternative to dummy coding with implications for higher education researchers

Abstract

The purpose of this article is to describe effect coding as an alternative quantitative practice for analyzing and interpreting categorical, racebased independent variables in higher education research. Unlike indicator (dummy) codes that imply that one group will be a reference group, effect codes use average responses as a means for interpreting information. This technique is especially appropriate for examining race, as such a process enables raced subgroups to be compared to each other and does not position responses of any raced group as normative— the standard against which all other race effects are interpreted. The issues raised here apply in any research context where a categorical variable without a natural reference group (e.g., college major) is a potential predictor in a regression model.