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Algina, James; Keselman, H. J.; Penfield, Randall D. – Educational and Psychological Measurement, 2006
Kelley compared three methods for setting a confidence interval (CI) around Cohen's standardized mean difference statistic: the noncentral-"t"-based, percentile (PERC) bootstrap, and biased-corrected and accelerated (BCA) bootstrap methods under three conditions of nonnormality, eight cases of sample size, and six cases of population…
Descriptors: Effect Size, Comparative Analysis, Sample Size, Investigations
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Cribbie, Robert A.; Keselman, H. J. – Educational and Psychological Measurement, 2003
Compared strategies for performing multiple comparisons with nonnormal data under various data conditions, including simultaneous violations of the assumptions of normality and variance homogeneity. Monte Carlo study results show the conditions under which different strategies are most appropriate. (SLD)
Descriptors: Comparative Analysis, Monte Carlo Methods, Nonparametric Statistics
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Keselman, H. J.; Toothaker, Larry E. – Educational and Psychological Measurement, 1974
Descriptors: Analysis of Variance, Comparative Analysis, Hypothesis Testing, Research Methodology
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Keselman, H. J.; And Others – Educational and Psychological Measurement, 1976
Compares the harmonic mean and Kramer unequal group forms of the Tukey test for various: (a) degrees of disparate group sizes, (b) numbers of groups, and (c) nominal significant levels. (RC)
Descriptors: Comparative Analysis, Probability, Sampling, Statistical Significance
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Lix, Lisa M.; Keselman, H. J. – Educational and Psychological Measurement, 1998
Comparison of six procedures to test for location equality among two or more groups when population variances are heterogeneous suggests that, when the variance homogeneity and normality assumptions are not satisfied, and the design is unbalanced, the use of any of these test statistics with the usual least squares estimators is not recommended.…
Descriptors: Comparative Analysis, Estimation (Mathematics), Least Squares Statistics, Research Design