Comparison of Nonparametric and Parametric Methods in Repeated Measures Designs - A
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期刊名称： Communication in Statistics- Simulation and Computation
作者： Tandon, P.K.,Moeschberger, M.L.
走遍美国字幕版年份： 2007年
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期号： 第2期
strawberry的复数关键词： Repeated measures designs;multivariate normal distribution;Gumbel''s bivariate exponential distribution;type I error rates;parametric andnhn
nonparametric tests
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escalator单人房>room是什么意思摘要：This study investigates the performance of parametric and nonparametric tests to analyze repeated measures designs. Both multivariate normal and exponential distributions were simulated for
varying values of the correlation and ten or twenty subjects within each cell. For multivariate normal distributions, the type I error rates were lower than the usual 0.05 level for nonparametric tests, whereas the parametric tests without the Greenhou-Geisr or the Huynh-Feldt adjustment produced slightly higher type I error rates. Type I error rates for nonparametric tests, for multivariate exponential distributions, were more stable than parametric, Greenhou-Geisr or Huynh-Feldt adjusted tests. For ten subjects within each cell, the parametric tests were more powerful than nonparametric tests. For twenty subjects per cell, the power
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