Multivariate analysis techniques employ various methods of optimally weighting variables to form composites. The interpretation of these composites in subsequent analyses is rarely straightforward, fraught with difficulties based upon the statistical properites of the estimated weights. This paper synthesizes interpretive guidelines for four…

Most discriminant function analyses provide a table of hits and misses with respect to classifications. Cohen's kappa coefficient is shown to be applicable to these tables and useful for setting confidence limits for the accuracy of the discriminant prediction. (Author/JKS)

Classification is a procedure through which individuals are classified as being members of a particular group based on a variety of independent variables. Two methods of makin such classifications are discussed; the quadratic method is seen to be superior to the linear under certain constraints. (JKS)

The revisions applied to the linear discriminant functions (LDF's) for computerized psychiatric diagnosis are discussed in terms of a comparison of the LDF model with decision tree models. It is concluded that each model has its own advantages and disadvantages. (Author/DEP)

This study was to validate a three-component alcohol attitude scale by testing its ability to discriminate between a sample of U.S. university students and their Egyptian counterparts. Forty-nine of 54 items, all three components, and the total instrument discriminated significantly between U.S. and Egyptian students. (Author/MT)

Production and judgment tasks were used to investigate five- through eight-year-old children's metalinguistic awareness of pragmatic rules concerning direct and indirect requests for action and information. Results showed several effects for age of child and for type of request. (Author/RH)

This study formulates a property of a quantification method, the principle of equivalent partitioning. When used with Guttman's principle of internal consistency, the combination allows the analysis of correlational data in terms of the variate(s) chosen by the investigator. Applications to multiple-choice, rank-order, and paired comparison data…

The technique of generalizing sample results in a classification study to large subpopulations of unequal sizes was examined. The usual output from the discriminant analysis routine in the Statistical Package for the Social Sciences was extended to handle the present statistical problems. Advantages of the technique were discussed. (Author/DWH)

A voting behavior model hypothesizing voting intention as an intervening variable which mediates the relationship between voter attitudes and voting behavior was examined in the framework of the general election in Israel. Voter attitudes were assessed via a new attitude scaling device. The model was tested primarily via discriminant analysis.…

This study of 28 males study was oriented to discriminating impotence of biogenic origins from psychogenic etiology on the basis of a psychological inventory, the DSFI. Evaluation of the increase in predictive efficiency with use of the DSFI revealed it to be of value in clinical assessment of male potency disorders. (Author)

The available methods for analyzing and interpreting data with multivariate analysis of variance are reviewed, and guidelines for their use are presented. Causal models that underlie the various methods are presented to facilitate the use and understanding of the methods. (Author/PN)

A linear regression function is developed for use in a classification procedure. The procedure is applied to faculty merit review data, resulting in an interpretable regression function and within-sample classifications as good as a four-funtion discriminant analysis. (Author/BW)

The coincidence hypothesis predicts that dissimilarity between objects that differ on two separable dimensions is larger than predicted from their unidimensional differences on the basis of triangle inequality and segmental additivity. The coincidence hypothesis was supported in two-dimensional stimuli studies. (Author/CM)