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Bachman, Jerald G. | 1 |
McMurray, Mary Anne | 1 |
Rodgers, Willard L. | 1 |
Thayer, Jerome D. | 1 |
Tracz, Susan M. | 1 |
Wongbundhit, Yuwadee | 1 |
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Thayer, Jerome D. – 1986
The stepwise regression method of selecting predictors for computer assisted multiple regression analysis was compared with forward, backward, and best subsets regression, using 16 data sets. The results indicated the stepwise method was preferred because of its practical nature, when the models chosen by different selection methods were similar…
Descriptors: Comparative Analysis, Computer Simulation, Mathematical Models, Multiple Regression Analysis
Tracz, Susan M.; And Others – 1986
The purpose of this paper is to demonstrate how multiple linear regression provides a viable statistical methodology for dealing with meta-analysis in general, and specifically with the issues of nonindependence and design complexity, such as multiple treatments. Since the F-test and t-test are special cases of the general linear model,…
Descriptors: Effect Size, Mathematical Models, Meta Analysis, Multiple Regression Analysis
McMurray, Mary Anne – 1987
This paper illustrates the transformation of a raw data matrix into a matrix of associations, and then into a factor matrix. Factor analysis attempts to distill the most important relationships among a set of variables, thereby permitting some theoretical simplification. In this heuristic data, a correlation matrix was derived to display…
Descriptors: Correlation, Factor Analysis, Factor Structure, Goodness of Fit
Wongbundhit, Yuwadee – 1984
Two approaches for conceptualizing and estimating a contextual model for analyzing student achievement are the separate equation approach and the single equation approach. The separate equation method determines the relationship between the individual-level independent variable and the individual-level dependent variable within each group. It then…
Descriptors: Academic Achievement, Comparative Analysis, Computer Simulation, Educational Research
Rodgers, Willard L.; Bachman, Jerald G. – 1986
This paper explores various procedures of panel data in the estimation of causal models. The reported analyses are from the Monitoring the Future study, a nationwide questionnaire survey of 16,000 to 17,000 high school seniors conducted annually since 1975. First, the parameters of causal models are estimated in which the dependent variables are…
Descriptors: Attitude Measures, Attribution Theory, Comparative Analysis, Drug Use