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On the use of the generalized t and generalized rank‐sum statistics in medical research
Author(s) -
Blair R. Clifford,
Morel Jorge G.
Publication year - 1992
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780110410
Subject(s) - wilcoxon signed rank test , rank (graph theory) , mathematics , statistics , type i and type ii errors , generalized linear model , statistical hypothesis testing , econometrics , combinatorics , mann–whitney u test
Abstract We have used Monte Carlo methods to compare the type I error properties of the conditional and unconditional versions of the generalized t and the generalized rank‐sum tests to those of the independent samples t and Wilcoxon rank‐sum tests. Results showed inflated type I errors for the conditional generalized tests but not for the unconditional tests. We also compared the power of the unconditional generalized tests to that of the t and Wilcoxon tests under a variety of conditions. Results showed the generalized tests to be much more efficient than their traditional counterparts in some circumstances, but substantially less powerful in others. Based on these and other considerations, we conclude that the application of these newer statistics in medical research needs further consideration.