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Wolters, Christopher A.; Fan, Weihua; Daugherty, Stacy G. – Journal of Experimental Education, 2013
This study was designed to forge stronger theoretical and empirical links between achievement goal theory and attribution theory. High school students ("N" = 224) completed a self-report survey that assessed 3 types of achievement goals, 7 types of attributions, and self-efficacy. Results indicated that students' adoption of achievement…
Descriptors: Goal Orientation, Attribution Theory, Self Efficacy, Academic Achievement
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Morris, John D.; And Others – Journal of Experimental Education, 1979
Three traditional methods of selection of variables to be included in a "best" regression equation are compared to a method designed to maximize weight validity. Implications for constructing regression equations for prediction are discussed, with consideration of the weight validity maximization method recommended in crucial situations.…
Descriptors: Academic Achievement, High Schools, Multiple Regression Analysis, Predictor Variables
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Huberty, Carl J. – Journal of Experimental Education, 1972
It is shown that in the special case of just two criterion groups the predictor variables may be equivalently ordered (with respect to contribution to prediction or discrimination) by the univariate F-ratios and by estimates of the predictor versus the linear discriminant function correlations. (Author)
Descriptors: Behavioral Science Research, Discriminant Analysis, Mathematical Applications, Multiple Regression Analysis
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Suddick, D. E. – Journal of Experimental Education, 1974
It is the purpose of this paper to investigate the chance nature of overfit as it relates to a regression formulation of research, to describe a model for projecting the overfit, and to empirically validate the model. (Author)
Descriptors: Correlation, Educational Research, Models, Multiple Regression Analysis
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Borich, Gary D. – Journal of Experimental Education, 1972
Paper reviews the test for regression lines and provides equations for expanding this test to regression planes. (Author)
Descriptors: Analysis of Covariance, Homogeneous Grouping, Mathematical Applications, Multiple Regression Analysis
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Janzen, Henry L.; Hallworth, Herbert J. – Journal of Experimental Education, 1973
The present study is an attempt to explore the usefulness of demographic predictors of writing ability. Specifically, it is concerned with delineating the elements involved in writing and to ascertain the effects of achievement, language background, age, sex, social class, etc., on linguistic ability. (Author/RK)
Descriptors: College Students, Demography, Factor Analysis, Multiple Regression Analysis
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Nelson, Larry R. – Journal of Experimental Education, 1979
The authors state that multiple regression is a powerful method of statistical analysis, provides a strength of relationship index, and should replace analysis of variance (ANOVA) in educational research. They also discuss the coding of categorical variables and available computer programs for multiple regression. (Author/MH)
Descriptors: Analysis of Variance, Classification, Comparative Analysis, Computer Programs
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Morris, John D.; Guertin, Wilson H. – Journal of Experimental Education, 1977
Common factor scores were compared to unfactored data-level variables as predictors in terms of the correlation of a criterion with the predicted value in multiple regression equations applied to replication (cross-validation) samples. (Editor)
Descriptors: Correlation, Educational Research, Factor Analysis, Factor Structure
Peer reviewed Peer reviewed
Kean, Donald K.; And Others – Journal of Experimental Education, 1987
Two experiments examined the role that college students' verbal aptitude and evaluation anxiety play in the production of persuasive letters. Results showed that verbal aptitude should be considered when predicting the quality of students writing. Taking writing anxiety into account did not increase the predictive power of verbal aptitude scores.…
Descriptors: College Students, Higher Education, Multiple Regression Analysis, Persuasive Discourse