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Lunneborg, Clifford E.; Tousignant, James P. – Multivariate Behavioral Research, 1985
This paper illustrates an application of Efron's bootstrap to the repeated measures design. While this approach does not require parametric assumptions, it does utilize distributional information in the sample. By appropriately resampling from study data, the bootstrap may determine accurate sampling distributions for estimators, effects, or…
Descriptors: Hypothesis Testing, Research Design, Research Methodology, Sampling

Eiting, Mindert H.; Mellenbergh, Gideon J. – Multivariate Behavioral Research, 1980
Using reasonable values for the parameters in both null and alternative hypotheses about covariance matrices, an optimal and feasible combination of number of subjects, significance level, and power of the test were determined for an empirical study of the measurement of musical ability. (Author/BW)
Descriptors: Education Majors, Foreign Countries, Higher Education, Hypothesis Testing

Green, Samuel B. – Multivariate Behavioral Research, 1991
An evaluation of the rules-of-thumb used to determine the minimum number of subjects required to conduct multiple regression analyses suggests that researchers who use a rule of thumb rather than power analyses trade simplicity of use for accuracy and specificity of response. Insufficient power is likely to result. (SLD)
Descriptors: Correlation, Effect Size, Equations (Mathematics), Estimation (Mathematics)