Using the General Linear Model to Facilitate the Full Integration of Qualitative and Quantitative Analysis: The Potential to Improve Prediction and Theory Building and Testing

Abstract

The data analysis phase of mixed methods research studies typically involves a quantitative analysis of quantitative data and a qualitative analysis of qualitative data, called non-crossover analysis. However, such non-crossover mixed analyses have one important flaw: they maintain the traditional dichotomous distinction between quantitative and qualitative analysis. Thus, what are needed are crossover mixed analyses in which the quantitative and qualitative data analyses are fully integrated. It is only by conducting such crossover mixed analyses that synechism—which represents an antidualistic stance wherein dichotomies are seen as being false and binaries are replaced with continua—can occur. Thus, in this article, we outline a crossover mixed analysis approach that involves the full integration of qualitative analyses with regression approaches.