A New and Simpler Approximation for ANOVA Under Variance Heterogeneity
Journal of Educational StatisticsPublished 1 June 1994
Ralph A. Alexander, Diane M. Govern
Citations125
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Abstract
A new approximation is proposed for testing the equality of k independent means in the face of heterogeneity of variance. Monte Carlo simulations show that the new procedure has Type I error rates that are very nearly nominal and Type II error rates that are quite close to those produced by James’s (1951) second-order approximation. In addition, it is computationally the simplest approximation yet to appear, and it is easily applied to Scheffé (1959) -type multiple contrasts and to the calculation of approximate tail probabilities.
Keywords
MathematicsDecision Sciences
Computers Environment and Urban SystemsStatistical power analysis for the behavioral sciences
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This note is concerned with a particular aspect of Monte Carlo computations, namely, with the generation of random variances and covariances in paired samples from a bivariate normal distribution.