Research has established that student-athletes drink more alcohol and experience greater consequences compared to their non-athlete peers, prompting many investigators to consider university athletes an "at risk" subpopulation of college students. However, a dearth of research exists on explaining drinking behavior among student-athletes…

Illustrates the use of discriminant analysis to identify the background factors among accepted applicants that best predict actual attendance. An illustration for MBA programs at the University of Hawaii showed the applicant's residence and tuition status were the best predictors. (JAC)

Used a current attrition study to show the usefulness of discriminative analysis and a cross validation technique applied to student nonpersister questionnaire respondents and nonrespondents. Results of the techniques allowed delineation of several areas of sample under-representation and established the instability of the regression weights…

Predicting MBA student performance for admission decisions is crucial for educational institutions. This paper evaluates the ability of three different models--neural networks, logit, and probit to predict MBA student performance in graduate programs. The neural network technique was used to classify applicants into successful and marginal student…

This study utilized data from the "NCES Beginning Postsecondary Students Longitudinal Study (BPS 96/01)" to explore the 6-year persistence status of Family and Consumer Sciences (FCS) students seeking the bachelor's degree at four-year institutions irrespective of whether they had remained at their initial institution, transferred, temporarily…