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Lai, Mark H. C.; Kwok, Oi-man – Journal of Experimental Education, 2015
Educational researchers commonly use the rule of thumb of "design effect smaller than 2" as the justification of not accounting for the multilevel or clustered structure in their data. The rule, however, has not yet been systematically studied in previous research. In the present study, we generated data from three different models…
Descriptors: Educational Research, Research Design, Cluster Grouping, Statistical Data
Dunn, Karee E.; Airola, Denise T.; Lo, Wen-Juo; Garrison, Mickey – Journal of Experimental Education, 2013
Data-driven decision-making (DDDM) reform has proven to be an effective means for improving student learning. However, little DDDM reform has happened at the classroom level, and little research has explored variables that influence teacher adoption of DDDM. The authors propose a model in which teachers' sense of efficacy for the skills that…
Descriptors: Data, Decision Making, Academic Achievement, Predictor Variables

Dunham, Randall B.; Kravetz, Dennis J. – Journal of Experimental Education, 1975
Descriptors: Correlation, Criteria, Data Analysis, Predictor Variables

Huberty, Carl J. – Journal of Experimental Education, 1975
An empirical comparison is made of three proposed indices of relative predictor variable contribution: (1) the scaled weights of the first discriminant function; (2) the total group estimates of the correlations between each predictor variable and the first function; and (3) the within-groups estimates of the correlations between each predictor…
Descriptors: Correlation, Data Analysis, Discriminant Analysis, Educational Research

Grobe, Cary H.; MacDonald, Ian S. – Journal of Experimental Education, 1975
The purpose of this investigation was to determine the contribution of factors such as: (1) high school science background; (2) interest in geology; (3) teacher characteristics; and (4) geology course background to performance on a measure of geology achievement. (Author)
Descriptors: Academic Achievement, Course Content, Data Analysis, Geology

Pohl, Norval Frederick – Journal of Experimental Education, 1974
The purpose of this study was to compare the relative classificatory ability of the Linear Discriminant Function (LDF) and the Bayesian Taxonomic Procedure (BTP) when these techniques are applied to multivariate normal and nonnormal data with differing degrees of overlap in the distributions of the predictor variables. (Editor)
Descriptors: Bayesian Statistics, Diagrams, Predictor Variables, Research Design

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

Mueller, Daniel J. – Journal of Experimental Education, 1974
The purpose of this study is to evaluate the effectiveness of materials developed for self instruction for a college course in educational measurement. (Author/RK)
Descriptors: Academic Achievement, Independent Study, Instructional Materials, Measurement

Sharon, Amiel T. – Journal of Experimental Education, 1972
The remedial course had no effect on student satisfaction and persistence but a modest effect on subsequent course performance. The experimental methodology described can provide the college researcher with a basis for determining whether there is a need to revise or eliminate current remdial courses. (Author)
Descriptors: College Students, Course Evaluation, Data Analysis, English

Houston, Samuel R.; And Others – Journal of Experimental Education, 1972
Study sought to determine the feasibility of using a modified form of Judgment Analysis (JAN) as a vehicle for identifying a policy of rated school effectiveness in the experimental League of Cooperating Schools (LCS) project. (Authors)
Descriptors: Evaluation Criteria, Evaluation Methods, Performance Specifications, Policy Formation

Henke, Raymond O. – Journal of Experimental Education, 1976
The purpose of this study was to determine characteristics of the disadvantaged client and of the Concentrated Employment Program (CEP) which related to the successful vocational training and placement of 150 unemployed public assistance recipients who were served by the San Antonio Concentrated Employment Program. (Editor)
Descriptors: Diagrams, Disadvantaged, Educational Research, Employment Programs

O'Reilly, Robert R. – Journal of Experimental Education, 1976
Examines the influence of one teacher personality variable, dogmatism, and one organizational variable, tenure status, on the resistance of teachers toward innovation. (Author/RK)
Descriptors: Dogmatism, Educational Innovation, Educational Research, Predictor Variables

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

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

Evans, Charles S. – Journal of Experimental Education, 1982
A linear regression model was used to test the relationship between the knowledge of Kohlberg's theory and moral stage development. A multiple regression analysis was used to test the multivariate relationship between one dependent and five independent variables. Neither analysis demonstrated a statistically significant relationship. (Author/PN)
Descriptors: Academic Achievement, Age, Data Analysis, Developmental Stages
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