Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1151273 | Statistical Methodology | 2008 | 13 Pages |
Abstract
We formulate rank statistics for testing hypotheses in unbalanced, and possibly heteroscedastic, two-factor nested designs with independent observations. These include Wald-type statistics based on the theory introduced by Akritas, Arnold and Brunner, as well as a Box-type approximation which is intended to improve the accuracy of approximation to asymptotic distributions. We also present statistics based on a recent theory of weighted FF-statistics for ranks. The actual sizes of the statistics at various nominal levels are compared in a simulation study. Our main conclusion is that the Box-adjusted Wald-type statistic is the only statistic that is accurate across all the situations considered and therefore we recommend it for general use.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
A. Stavropoulos, C. Caroni,