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…

The author explored whether 3 workplace conditions were related to teacher mobility decisions. The modeling strategy incorporated a series of binomial and multinomial logistic models to estimate the effects of administrative support, classroom control, and behavioral climate on teachers' decisions to quit teaching or switch schools. The results…

A family of solutions for linear relations among k sets of variables is proposed. Solutions are compared with respect to their optimality properties. For each solution the appropriate stationary equations are given. For one example it is shown how the determinantal equation of the stationary equations can be interpreted. (Author/BW)

Commonality components have been defined as a method of partitioning squared multiple correlations. The asymptotic joint distribution of all possible squared multiple correlations is derived. The asymptotic joint distribution of linear combinations of squared multiple correlations is obtained as a corollary. (Author/JKS)

An extension of Wollenberg's redundancy analysis (an alternative to canonical correlation) is proposed to derive Y-variates corresponding to the optimal X-variates. These variates are maximally correlated with the given X-variates, and depending upon the standardization chosen they also have certain properties of orthogonality. (Author/JKS)

Recent theoretical analyses of the concept of suppression are identified and discussed. A generalized definition of suppression is presented and the conditions for suppressor structures in the context of the General Linear Model are derived. (Author)

A new algorithm is used to test and describe the set of all possible solutions for any linear model of an empirical ordering derived from techniques such as additive conjoint measurement, unfolding theory, general Fechnerian scaling, and ordinal multiple regression. The algorithm is computationally faster and numerically superior to previous…

Using a degenerate multivariate normal model for the distribution of organismic variables, the form of least-squares regression analysis required to estimate a linear functional relationship between variables is derived. It is suggested that the two conventional regression lines may be considered to describe functional, not merely statistical,…

Bayesian analysis of an m-group model is considered. A convenient stage III prior is proposed, and cases when the posterior distributions take on a simple form are exhibited. The behavior of various point estimators of the linear parameters of the model are explored in a Monte Carlo study. In the simple model considered, the O'Hagan estimator…

A statistical analysis procedure is developed, based on the notion that many educational programs are dynamic interventions in natural growth processes, and is called value-added analysis. The theory of value-added analysis, and several applications are presented. (Author/JKS)

When sample sizes and/or X intervals are unequal, the analysis of variance computations for trend analysis become quite complicated. This article shows how multiple regression/correlation analysis may be applied in order to accomplish with great simplicity trend analysis under "irregular" conditions. (Author/RL)

Fifteen examples using different formulas for calculating degrees of freedom for power analysis of multiple regression designs worked out by Cohen are presented, along with a more general formula for calculating such degrees of freedom. (Author/JKS)

This paper shows that redundancy maximization with J. K. Johansson's extension can be accomplished via a simple iterative algorithm based on H. Wold's Partial Least Squares. The model and the iterative algorithm for the least squares approach to redundancy maximization are presented. (TJH)

Common applications of the part correlation coefficient are in causal regression models and estimation of suppressor variable effects. However, there is no statistical test of the significance of the difference between a zero-order correlation and a part correlation, nor between a pair of part correlations. Hotelling's t is used for contrasting:…

A definition of a suppressor variable is presented which is based on the relation of the semipartial correlation to the zero order correlation. Advantages of the definition are given. (Author/JKS)