A method for comparing the cross-validated classification accuracy of Fisher's linear classification functions (FLCFs) and the least absolute deviation is presented under varying data conditions for the two-group classification problem. With this method, separate-group as well as total-sample proportions of current classifications can be compared…

The use of stepwise methodologies has been sharply criticized by several researchers, yet their popularity, especially in educational and psychological research, continues unabated. Stepwise methods have been considered particularly well suited for use in regression and discriminant analyses, but their use in discriminant analysis (predictive…

Cross-validation, an economical method for assessing whether sample results will generalize, is discussed in this paper. Cross-validation is an invariance technique that uses two subsets of the data sample to derive discriminant function coefficients. The two sets of coefficients are then used with each data subset to derive discriminant function…

One of the greatest problems that has confronted the physical education profession is that of evaluating sport skill tests and their relationship to successful performance. This study was thus undertaken to investigate the relationship of basketball skill tests and player biographic data to success in playing basketball. Ninety-four subjects ages…

Three paired-associate learning studies were run to compare signal detection analysis of recall and recognition memory performance. Experiment I showed that (a) rates of recall and recognition discriminability are substantially different in later trials and (b) a previously suggested correction for guessing does not transform the data to…

The process of discriminant analysis is reviewed in four different aspects: focusing on formulations, interpretations, and uses of discrimination, estimation and classification. Other issues, problems, and recent developments in discriminant analysis are also reviewed. (Author/DEP)

Presents maximum-likelihood confirmatory factor analysis (CFA) as a means for interpreting complete and incomplete multitrait-multimethod designs. CFA was applied to four data sets representing four designs and to an artificial data set to demonstrate its use in test validation designs to assess discriminant, convergent, and construct validity.…

A modified automatic interaction detector (MAID) was combined with discriminant analysis (DA) to form MAIDDA and to determine whether it might improve classification results over classical DA methods. Application of MAIDDA to the 1983 and 1984 Air Force Academy's graduating classes (N = 3,012) showed that it is a promising clustering technique.…

Investigates the use of the Bayley Infant Behavior Record (IBR) with premature and full-term infants. Analysis of the two discriminant functions obtained from the discriminant analysis appear to substantiate the claim that the IBR is an index of cognitive test-taking behaviors, which can be used reliably with preterm and full-term infants.…

Describes an algorithm for the calculation of term discrimination values that may be used when the interdocument similarity measure used is the cosine coefficient and when the document representations have been weighted using one particular term weighting scheme. (7 references) (Author/CLB)

Discriminated three groups of neuropsychiatric outpatients (N=138) using a measure of aggression formed by summing subscales of the Minnesota Multiphasic Personality Inventory. Results indicated that the group differences cannot be attributed to more general factors such as age, sex, education, IQ or degree of overall psychopathology. (LLL)

Subjected sequences of violent and nonviolent offenses to log-linear analyses of the stabilities and magnitudes of their transition probabilities. Results were seen to support previous research in which nonviolent criminality emerged as more fundamental than violence in potential for pattern development. (LLL)

This paper outlines two types of discriminant analysis, predictive discriminant analysis (PDA) and descriptive discriminant analysis (DDA). Important differences between PDA and DDA are introduced and discussed using a heuristic data set, specifically indicating the portions of the Statistical Package for the Social Sciences (SPSS) output relevant…

A review of the literature reveals that important statistical algorithms and indices pertaining to logistic regression are being underused. This paper describes logistic regression in comparison with discriminant analysis and linear regression, and suggests that some techniques only accessible through computer syntax should be consulted in…

This study compared the classification performance among parametric discriminant analysis, nonparametric discriminant analysis, and logistic regression in a two-group classification application. Field data from an organizational survey were analyzed and bootstrapped for additional exploration. The data were observed to depart from multivariate…