Several advantages to the use of different kinds of factor scores as independent variables in a multiple regression equation are reported. A computer program is presented which will calculate a regression equation using a variety of factor scores. (Author/JKS)

This study compared double cross-validation replication predictive accuracies of six types of factor scores with full-rank data by utilizing data in which classroom achievement was predicted from affective and cognitive variables. Prediction was significantly more accurate for factor scores than for full-rank data. (Author/CP)

Several advantages to the use of factor scores as independent variables in a multiple regression equation were found. To help select the most desirable type of factor score on which to calculate a regression equation, computer-based Monte Carlo methods were used to compare the predictive accuracy upon replication of regression of five…

Common factor scores were compared to unfactored data-level variables as predictors in terms of the correlation of a criterion with the predicted value in multiple regression equations applied to replication (cross-validation) samples. (Editor)

Computer-based Monte Carlo methods compared the predictive accuracy upon replication of regression of five complete and four incomplete factor score estimation methods. Prediction on incomplete factor scores showed better double cross-validated prediction accuracy than on complete scores. The unique unit-weighted factor score was superior among…