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Keselman, H. J.; Algina, James – Multivariate Behavioral Research, 1997
Examines the recommendations of H. Keselman, K. Carriere, and L. Lix (1993) regarding choice of sample size for obtaining robust tests of the repeated measures main and interaction hypotheses in a one Between-Subjects by one Within- Subjects design with a Welch-James type multivariate test when covariance matrices are heterogeneous. (SLD)
Descriptors: Analysis of Covariance, Interaction, Multivariate Analysis, Research Design
Peer reviewed Peer reviewed
Bandalos, Deborah L. – Multivariate Behavioral Research, 1993
A Monte Carlo study investigated the use of four cross-validation indices with confirmatory factor analysis models. Influences of sample size, loading size, and degree of model misspecification were studied. Larger sample sizes and better specified models result in better cross-validation results. (SLD)
Descriptors: Equations (Mathematics), Estimation (Mathematics), Influences, Mathematical Models
Peer reviewed Peer reviewed
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)