ABSTRACT
Multiple Linear Regression Analysis with Qualitative Data that have been Quantitized between a dependent variable and two or more independent variables. Specifically, it allows researchers to predict values and/or explain variation in the dependent variable using continuous and/or categorical independent variables, including those that have been quantitized from qualitative data. The flexibility and capabilities of multiple linear regression make it well suited for mixed analyses. This chapter provides an overview of ordinary least squares regression models with a particular emphasis on multiple linear regression incorporating qualitative data. The chapter builds a conceptual definition of regression, then describes the process of quantitizing qualitative data so that it is suitable for use in regression-based analyses. Technical details are offered that cover model specification, estimation, and interpretation of results. An empirical example of regression with quantitized data, dealing with associations between implementation fidelity and school poverty levels, is used to illustrate the use of a combination of quantitative and quantitized qualitative information. Suggested applications, strengths and limitations, and additional resources are provided at the conclusion of the chapter.
