How to compute and report subscores for a test that was originally designed for reporting scores on a unidimensional scale has been a topic of interest in recent years. In the research reported here, we describe an application of multidimensional item response theory to identify a subscore structure in a test designed for reporting results using a…

The perfunctory use of factor scores in conjunction with regression analysis is inappropriate for many purposes. It is suggested that factoring methods are most suitable for independent variable sets when some consideration has been given to the nature of the domain, which is implied by the predictors. (Author/BW)

EXPLORE is a flexible computer program for analyzing multiple data sets. The investigator has the option of focusing on the original variables, or of selecting a reduced rank solution where original variables are summarized by a principal components analysis. (Author/JKS)

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)

Factor scale scores are sometimes used as weights to create composite variables representing the variables included in a factor analysis. If these composite variables are then used to predict some dependent variable, serious theoretical and methodological problems arise. This paper explores these problems and suggests strategies for circumventing…

Variables used in applicant selection into the British Civil Service were analyzed for a sample using varimax factor analysis, multidimensional scaling and multiple regression. Results indicated that four dimensions or factors of applicant selection were consistent across a variety of settings and analyses. (JKS)

It is shown how partial covariance, part and partial correlation, and regression weights can be estimated and tested for significance by means of a factor analytic model. Comparable partial covariance, correlations, and regression weights have identical significance tests. (Author)

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)

Three approaches to the prediction of juvenile recidivism--factor analysis, stepwise multiple regression, and stepwise discriminant analysis--are contrasted. Stepwise discriminant analysis provided the most consistent selection of variables in the data set used. Problems and advantages of the three approaches are discussed. (Author/JKS)