Predicting student academic performance has long been an important research topic in many academic disciplines. The present study is the first study that develops and compares four types of mathematical models to predict student academic performance in engineering dynamics--a high-enrollment, high-impact, and core course that many engineering…

Major objective in this study was the structuring of a predictive model that would assess combinations of variables that most effectively and parsimoniously measure and forecast college success. (Author)

The uses and restrictions of commonality analysis are described. Commonality analysis has been increasingly used as a method to examine the relative importance of independent variables, through the partitioning of variance among the variables of the regression equation into unique and common components. The effects of all other independent…

Study examined models for improving prediction of single and multiple criteria. (Author)

Purpose of this investigation was to determine whether the inclusion of quadratic and/or interaction terms in a regression model would improve the prediction of student nurses' grade point averages. (Authors)

Adaptive forms of weighted structural regression are developed and discussed. Bootstrapping studies indicate that the new methods have potential to recover known population regression weights and predict criterion score values routinely better than do ordinary least squares methods. The new methods are scale free and simple to compute. (SLD)

A model is proposed for investigating test validity as a predictor of a criterion variable when there are both missing and censored scores in the data set. Implications for maximum likelihood estimation are discussed, and the method is illustrated with hypothetical data sets. (SLD)

The Mahalanobis distance model was compared with the linear discriminant function model and found to provide very similar results, even when a number of the variables were binary. A group of college freshmen were categorized into two groups: 116 "leavers," students who did not return for the second year, and 269 "returners."…

The inter-battery factor analysis model for predictive systems appears to offer a useful formalization of these systems and provides some guides for the development of the system. (Author)

This paper discusses the principles underlying discriminant analysis and constructs a simulated data set to illustrate its methods. Discriminant analysis is a multivariate technique for identifying the best combination of variables to maximally discriminate between groups. Discriminant functions are established on existing groups and used to…

The development of new statistical methods of log-linear models by Leo Goodman has led to major advances in the statistical analysis of categorical data. Goodman's logit analysis, (the simplest form of log-linear models) can be applied in evaluation studies to estimate the "main effects" and "interaction effects" of categorical…

The existence of differential prediction of two-year grade point average is reported for gender groups within programs of study at the University of Iowa. Academic records of all freshmen entering the University in 1978 in the fields of Business, Liberal Arts, Pre-Medicine, and those undecided as to major were analyzed with respect to American…

Comparative applications of simple and complex faculty flow models are examined to determine (1) their relative demands for data and calculations, (2) the divergence of their projections, especially when modelling a no-growth faculty, and (3) an estimate of the error incurred (i.e., the cost to analysis) when a simple model is used. The results…

The purpose of the study was to develop a linear programming model to be used for prediction, test the accuracy of the predictions, and compare the accuracy with that produced by curvilinear multiple regression analysis. (Author)

This final report summarizes past research and suggests new approaches to the problem of estimating long-term individual constants using path analysis. The general objective of the research was to detect and measure the likelihood that one variable, x, measured at time, t, has a causal influence on another variable, y, measured at a subsequent…