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Algina, James; Keselman, H. J.; Penfield, Randall D. – Educational and Psychological Measurement, 2010
The increase in the squared multiple correlation coefficient ([delta]R[superscript 2]) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. Algina, Keselman, and Penfield found that intervals based on asymptotic principles were typically very inaccurate, even though the sample size…
Descriptors: Computation, Statistical Analysis, Correlation, Statistical Inference
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Algina, James; Keselman, H. J. – Educational and Psychological Measurement, 2008
Applications of distribution theory for the squared multiple correlation coefficient and the squared cross-validation coefficient are reviewed, and computer programs for these applications are made available. The applications include confidence intervals, hypothesis testing, and sample size selection. (Contains 2 tables.)
Descriptors: Intervals, Sample Size, Validity, Hypothesis Testing
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Algina, James; Keselman, H. J.; Penfield, Randall D. – Educational and Psychological Measurement, 2007
The increase in the squared multiple correlation coefficient ([Delta]R[squared]) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. The coverage probability that an asymptotic and percentile bootstrap confidence interval includes [Delta][rho][squared] was investigated. As expected,…
Descriptors: Probability, Intervals, Multiple Regression Analysis, Correlation
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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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Kowalchuk, Rhonda K.; Keselman, H. J.; Algina, James; Wolfinger, Russell D. – Educational and Psychological Measurement, 2004
One approach to the analysis of repeated measures data allows researchers to model the covariance structure of their data rather than presume a certain structure, as is the case with conventional univariate and multivariate test statistics. This mixed-model approach, available through SAS PROC MIXED, was compared to a Welch-James type statistic.…
Descriptors: Interaction, Sample Size, Statistical Analysis, Evaluation Methods
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Keselman, Joanne C.; Keselman, H. J. – Educational and Psychological Measurement, 1987
The power to detect main and interaction effects in a factorial design was determined when the Bonferroni method was used to control the overall rate of Type I error. For sample sizes typical of educational research, the power of this procedure was considerably less than that of recommended standards. (TJH)
Descriptors: Educational Research, Sample Size, Statistical Analysis