Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences, 3rd Edition

16

Multiple Dependent Variables: Set Correlation

16.1  INTRODUCTION TO ORDINARY LEAST SQUARES TREATMENT OF MULTIPLE DEPENDENT VARIABLES

In Chapter 5 and subsequent sections of this book we have discussed the analytic utility of thinking of independent variables as members of a smaller number of sets. These sets, each of which may have one or more members, may represent a distinct role in the research, such as a set of potential confounders (common causes of independent and dependent variables) or control variables, whose central role is to rule out certain alternative reasons for a relationship between Y and the IVs of interest. Alternatively, they may represent the multiple facets or aspects of a research construct, as, for example demographic ...