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Peer reviewedGames, Paul A. – American Educational Research Journal, 1971
See EJ 041 277 for original article. (DG)
Descriptors: Analysis of Variance, Hypothesis Testing, Research Methodology, Statistical Analysis
Peer reviewedElster, Richard S.; Dunnette, Marvin D. – Educational and Psychological Measurement, 1971
Descriptors: Hypothesis Testing, Measurement Techniques, Probability, Sampling
Peer reviewedGames, Paul A. – American Educational Research Journal, 1971
Twelve multiple comparison tests, both simultaneous and sequential, are described, analyzed, and evaluated. Overall recommendations are presented in a flow-diagram. (DG)
Descriptors: Analysis of Variance, Hypothesis Testing, Research Methodology, Statistical Analysis
Roberge, James J. – Educ Psychol Meas, 1970
This nonparametric analysis of variance program includes the Kruskal-Wallis, Friedman, and Cochran methods. (DG)
Descriptors: Analysis of Variance, Computer Programs, Nonparametric Statistics, Statistical Analysis
Smith, Robert A.; And Others – Educ Psychol Meas, 1970
Descriptors: Analysis of Variance, Computer Programs, Nonparametric Statistics, Statistical Analysis
Peer reviewedBerenson, Mark L. – Psychometrika, 1982
The statistical power of nine k-sample tests against ordered location alternatives under completely randomized designs are investigated. The results are intended to aid researchers in selecting appropriate statistical procedures. (Author/JKS)
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Research Design
Peer reviewedHuberty, Carl J.; Holmes, Susan E. – Educational and Psychological Measurement, 1983
An alternative analysis of the two-group single response variable design is proposed. It involves the classification of experimental units to populations represented by the two groups. Three real data sets are provided to illustrate the utility of the classification analysis. A table of sample sizes required for the analysis is presented.…
Descriptors: Classification, Data Analysis, Hypothesis Testing, Research Design
Peer reviewedRenner, Barbara Rochen; Ball, Donald W. – Educational and Psychological Measurement, 1983
To determine the effect of violating the assumption of homogeneity of covariance for the Tukey Wholly Significant Difference (WSD) test, Monte Carlo simulations varied the number of treatment groups, sample size, and degree of covariance heterogeneity. As covariance heterogeneity was increased, the empirical significance levels increased beyond…
Descriptors: Data Analysis, Hypothesis Testing, Monte Carlo Methods, Research Methodology
Peer reviewedHaase, Richard F. – Educational and Psychological Measurement, 1983
This paper reviews the distinctions between classical and partial eta square and derives a formula for use in those complex analysis of variance designs in which the investigator desires a measure of classical eta square and has access only to the F-tests and relevant degrees of freedom. (Author/BW)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Formulas, Research Design
Peer reviewedRoss, Donald C. – Educational and Psychological Measurement, 1983
Theta is a statistic which measures the degree to which a designated pattern successfully partitions a matrix of pre- and post-treatment ratings into regions typical of each of two treatments. In this paper, theta is extended to multivariate and multigroup cases. (Author/BW)
Descriptors: Hypothesis Testing, Matrices, Multivariate Analysis, Research Methodology
Peer reviewedFagley, N. S.; McKinney, I. Jean – Journal of Counseling Psychology, 1983
Reexamines the article by Atkinson, Furlong, and Wampold (1982) and questions their conclusion that reviewers were biased toward statistically significant results. A statistical power analysis shows the power of their bogus study was low. Low power in a study reporting nonsignificant findings is a valid reason for recommending not to publish.…
Descriptors: Bias, Evaluation Criteria, Opinions, Publications
Peer reviewedKeselman, H. J. – Multivariate Behavioral Research, 1982
The need for multiple comparison procedures for repeated measures means employing a pooled estimate of error variance to conform to the sphericity assumptions of the design in order to provide a valid test is discussed. An alternative approach which does not require this assumption is presented. (Author/JKS)
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Research Design
Peer reviewedYu, Mimi C.; Dunn, Olive Jean – Educational and Psychological Measurement, 1982
Eight asymptotically robust tests of population correlation coefficient equality are proposed and are studied along with two parametric tests. Monte Carlo simulation is used to compare the small sample performance of these ten procedures. The sampled distributions consist of the normal distribution, two mixed normal distributions and four…
Descriptors: Correlation, Mathematical Formulas, Statistical Distributions, Statistical Significance
Peer reviewedRae, Gordon – Educational and Psychological Measurement, 1982
Analyses of artificial data involving repeated, related binary measures to different samples suggest that Tideman's generalized chi-square statistic and conventional repeated-measures analysis of variance do not produce conflicting outcomes. Provided the appropriate assumptions are met, analysis of variance may provide a more versatile approach.…
Descriptors: Analysis of Variance, Hypothesis Testing, Research Design, Statistical Analysis
Peer reviewedRonis, David L. – Educational and Psychological Measurement, 1981
Many researchers draw the conclusion that one independent variable has more impact than another without testing the null hypothesis that their impact is equal. This paper presents and recommends a technique for testing the relative magnitude of effects, rather than basing conclusions solely on descriptive statistics. (Author/BW)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Research Design


