In certain data analyses (e.g., multiple discriminant analysis and multinomial log-linear modeling), classification decisions are made based on the estimated posterior probabilities that individuals belong to each of several distinct categories. In the Bayesian network literature, this type of classification is often accomplished by assigning…

A total of 149 students enrolled in an undergraduate nursing research methods course participated in a study comparing three strategies for using formative evaluation (test feedback throughout a course) to predict students at risk of failure at summative evaluation (the final examination). Students took 12 weekly multiple-choice quizzes, which…

Least squares and Bayes methods were used in a cross validation study conducted for comparison purposes. The study applies to situations with the following conditions: predictor data are given on the same scales; criterion data may be given on different scales; and it is necessary to pool data even though criterion scale differences exist. Such a…

Classical multiple regression was compared with Bayesian m-group regression, complete with cross-validation. The setting was a post-developmental studies situation in a comprehensive community college. A secondary purpose of the study was to incorporate an advisor prediction of grade point average (GPA) as input into both regression procedures.…

Classical statistical methods and the small enrollments in graduate departments have constrained the Graduate Record Examinations (GRE) Validity Study Service to providing only validities for single predictors. Estimates of the validity of two or more predictors, used jointly, are considered too unreliable because the corresponding prediction…

Methods for predicting specific college course grades, based on small numbers of observations, were investigated. These methods use collateral information across potentially diverse institutions to obtain refined within-group parameter estimates. One method, referred to as pooled least squares with adjusted intercepts, assumes that slopes and…

The purpose of this study was to present and evaluate Bayesian-type models for estimating probabilities of program completion and for predicting first quarter grade point averages of community college students entering certain allied health fields. Two Bayesian models were tested. Bayesian Model 1--Estimating Probabilities of Program…

A validity study with 5,219 students examined the degree to which Graduate Management Admission Test (GMAT) scores and undergraduate grade point average (GPA) could predict first-year average and final GPA in doctoral programs in business. The usefulness of the predictions derived from the empirical Bayes regression models is discussed. (SLD)

Two methods of using collateral information from similar institutions to predict college freshman grade average were investigated. One central prediction model, referred to as pooled least squares with adjusted intercepts, assumes that slopes and residual variances are homogeneous across selected colleges. The second model, referred to as Bayesian…

Due to factors such as high enrollment demands, limited institutional space, and high program costs, certain admissions requirements in the guidance/selection of students for health technology programs at Virginia Western Community College (VWCC) have become necessary. A Health Technology Admissions Evaluation System was created to develop and…

The validity of American College Testing Program (ACT) test scores and self-reported high school grades for predicting grades in specific college freshman courses was studied. Specific course grades are typically used to place students in remedial, standard, or advanced classes. These placement decisions, in turn, have immediate implications for…