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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Robustness, Power And Interpretability Of Pairwise Tests Of Discriminant Functions In Manova, Philip H. Ramsey, Patricia P. Ramsey, Priscila Hachimine, Nancy Andiloro
Robustness, Power And Interpretability Of Pairwise Tests Of Discriminant Functions In Manova, Philip H. Ramsey, Patricia P. Ramsey, Priscila Hachimine, Nancy Andiloro
Journal of Modern Applied Statistical Methods
Limiting follow-up hypotheses to be tested can reduce problems relating to the control of Type I and Type II errors in multivariate analysis of variance (MANOVA). Such limitations can also improve the interpretability of results. The importance of sample size, shape of population distribution, within-group correlations and heterogeneity of variances are demonstrated. The protected greatest characteristic root (GCR) procedure is shown to work well for small, group size, N (≤ 10). The unprotected GCR is shown to work well for larger N.
Jmasm31: Manova Procedure For Power Calculations (Spss), Alan Taylor
Jmasm31: Manova Procedure For Power Calculations (Spss), Alan Taylor
Journal of Modern Applied Statistical Methods
D’Amico, Neilands & Zambarano (2001) showed how the SPSS MANOVA procedure can be used to conduct power calculations for research designs. This article demonstrates a simple way of entering data required for power calculations into SPSS and provides examples that supplement those given by D’Amico, Neilands & Zambarano.