Prediction of Grade Point Averages in Nursing Schools Using Second‐order Multiple Regression Models

The present study was concerned with the prediction of first year grade point averages of associate degree nursing students. The primary objective of this investigation was to determine whether the inclusion of quadratic and/or interaction terms in a regression model would improve the prediction of student nurses’ grade averages. The predictor battery included cognitive, biographical, and personality variables. Results indicated that interaction and quadratic terms improve both the predictability of grade point averages and the replicability of these predictions. The inclusion of higher order terms in prediction research is suggested as a means of improving predictive efficiency.