This article describes the early outcomes of an ongoing project at the University of South Florida in Tampa that involves using a logistics regression formula derived from pre-matriculation characteristics to predict the risk of individual student attrition. In this piece, the authors will describe the results of the prediction formula and the…

The important and sometimes difficult-to-grasp concept of regression suppressor variable effects is explored. An inquiry into the phenomenon of suppressor effects is accomplished via a synthesis of the existing literature and the use of a small heuristic data set to improve the accessibility of the concept. Implications for researchers are also…

A key strength of latent curve analysis (LCA) is the ability to model individual variability in rates of change as a function of 1 or more explanatory variables. The measurement of time plays a critical role because the explanatory variables multiplicatively interact with time in the prediction of the repeated measures. However, this interaction…

The number of regression studies being employed in sex discrimination cases is increasing. The need for caution in the case of multiple regression must be emphasized. Statistical concerns in sex discrimination cases are highlighted. (MLW)

This article presents an in-class Monte Carlo demonstration, designed to demonstrate to students the implications of multicollinearity in a multiple regression study. In the demonstration, students already familiar with multiple regression concepts are presented with a scenario in which the "true" relationship between the response and…

Rectifies the unsatisfactory textbook treatment of the finite-sample proprieties of estimators of regression models with a lagged dependent variable and autocorrelated disturbances. Maintains that the bias of the ordinary least squares estimator is determined by the dynamic and correlation effects. (MJP)

A salary prediction model for college faculty that is used at Georgia State University was reviewed and tested using multiple regression analysis. Various model specifications, incorporating academic rank, academic discipline, and academic experience, including professional and personal background characteristics, are reviewed. Academic rank is an…