The need for using invariance procedures to establish the external validity or generalizability of statistical results has been well documented. Invariance analysis is a tool that can be used to establish confidence in the replicability of research findings. Several approaches to invariance analysis are available that are broadly applicable across…

Canonical correlation analysis is a multivariate statistical model which facilitates the study of interrelationships among multiple dependent variables and multiple independent variables. It identifies components of one set of variables that are most highly related linearly to the components of the other set of variables. The underlying logic of…

This paper outlines procedures used to derive variables from data in the National Survey of Postsecondary Faculty; these variables were then used to create measures not expressly included as items in that survey. The derived variables were used to examine faculty satisfaction in two contexts: first, the complexity of satisfaction, and second, the…

Asserts that traditional approaches to multivariate analysis, including standard linear regression techniques, ignore the special character of count data. Explicates three suitable alternatives to standard regression techniques, a simple Poisson regression, a modified Poisson regression, and a negative binomial model. (MJP)

This monograph covers the theory, application, and interpretation of both descriptive and inferential statistical techniques in institutional research. Each chapter opens with a hypothetical case study, which is used to illustrate the application of one or more statistical procedures to typical research questions. Chapter 2 covers the comparison…