The type I error rate in stepwise regression analysis deserves serious consideration by researchers. The problem-wide error rate is the probability of selecting any variable when all variables have population regression weights of zero. Appropriate significance tests are presented and a Monte Carlo experiment is described. (Author/CTM)

The utility of a nonlinear transformation of the criterion variable in multiple regression analysis is established. A well-known law--the Pythagorean Theorem--illustrates the point. (Author/JKS)

This paper discusses how full model dummy variables can be used with partial correlation or multiple regression procedures to compute matrices of pooled within-group correlations. (Author/CTM)

The use of multiple regression analysis was compared to the use of discriminant function analysis in the prediction of college faculty rank. The multiple regression technique was shown to be generally superior in this instance. (JKS)

The inclusion of unmeasured variables in path analyses in educational research is discussed. The statistical basis for inclusion is presented, along with several examples. (JKS)

The relative magnitudes of R-squared values computed through multiple regression models using grade equivalent scores, raw scores, standard scores, and percentiles as both predictor and criterion variables are compared. Grade equivalents and standard scores produced the highest R-squared values. (Author/JKS)