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Li, Jian; Lomax, Richard G. – Journal of Experimental Education, 2011
Users assume statistical software packages produce accurate results. In this article, the authors systematically examined Statistical Package for the Social Sciences (SPSS) and Statistical Analysis System (SAS) for 3 analysis of variance (ANOVA) designs, mixed-effects ANOVA, fixed-effects analysis of covariance (ANCOVA), and nested ANOVA. For each…
Descriptors: Social Sciences, Computer Software, Statistical Analysis, Models
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Harwell, Michael; Maeda, Yukiko – Journal of Experimental Education, 2008
There is general agreement that meta-analysis is an important tool for synthesizing study results in quantitative educational research. Yet, a shared feature of many meta-analyses is a failure to report sufficient information for readers to fully judge the reported findings, such as the populations to which generalizations are to be made,…
Descriptors: Educational Research, Meta Analysis, Research Methodology, Statistical Analysis
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McNeil, Keith A.; Kelly, Francis J. – Journal of Experimental Education, 1970
Descriptors: Data Analysis, Psychometrics, Statistical Analysis
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Williams, John D. – Journal of Experimental Education, 1979
Hollingsworth recently showed a posttest contrast for analysis of variance situations that, for equal sample sizes, had several favorable qualities. However, for unequal sample sizes, the contrast fails to achieve status as a maximized contrast; thus, separate testing of the contrast is required. (Author/GSK)
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Statistical Analysis
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Huck, Schuyler W.; Sandler, Howard M. – Journal of Experimental Education, 1973
The present authors argued that the covariance analysis is completely valid even if there is a true main effect for pretesting and a second point of the paper involved a recommendation for data analysis if the interaction from ANOVA was significant. (Editor/RK)
Descriptors: Analysis of Covariance, Analysis of Variance, Data Analysis, Educational Research
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Katz, Barry M.; McSweeney, Maryellen – Journal of Experimental Education, 1984
This paper developed and illustrated a technique to analyze categorical data when subjects can appear in any number of categories for multigroup designs. Post hoc procedures to be used in conjunction with the presented statistical test are also developed. The technique is a large sample technique whose small sample properties are as yet unknown.…
Descriptors: Data Analysis, Hypothesis Testing, Mathematical Models, Research Methodology
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Engel, Barney M.; Cooper, Martin – Journal of Experimental Education, 1971
A study designed to compare the academic achievement of pupils in graded and non-graded schools using an Index of Non-gradedness to determine the validity of the term non-graded" as applied to some schools. (Author/RY)
Descriptors: Academic Achievement, Data Analysis, Elementary Schools, Nongraded Instructional Grouping
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Holdaway, Edward A. – Journal of Experimental Education, 1971
To assess whether different response patterns were associated with differences in the naming and placement of response categories, 1000 undergraduate students in educational administration completed a 10-item personal-values questionnaire. (Author)
Descriptors: Attitudes, Behavior Rating Scales, Data Analysis, Questionnaires
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Katz, Barry M.; McSweeney, Maryellen – Journal of Experimental Education, 1979
Errors of misclassification and their effects on categorical data analysis are discussed. The chi-square test for equality of two proportions is examined in the context of errorful categorical data. The effects of such errors are illustrated. A correction procedure is developed and discussed. (Author/MH)
Descriptors: Classification, Data Analysis, Data Collection, Error Patterns