One-sided multiple endpoint testing in two-sample comparisons
Titel:
One-sided multiple endpoint testing in two-sample comparisons
Auteur:
Reitmeir, Peter Wassmer, Gernot
Verschenen in:
Communications in statistics
Paginering:
Jaargang 25 (1996) nr. 1 pagina's 99-117
Jaar:
1996
Inhoud:
This article reviews several methods for comparing two treatments with multiple endpoints that take into account the dependence structure among the endpoints and that are sensitive to the multivariate one-sided alternative. The methods are classified into procedures that adjust sin-gle endpoint P-values separately, into bootstrap procedures that adjust single endpoint P-values through resampling from the whole data, and into procedures that summarize the data into a global test statistic. In this context, we describe step-down procedures leading to conclusions about the single endpoints. Applying the closed test principle, James (1991, Statistics in Medicine 10, 1123-1135)-based, O'Brien (1984, Biometries 40, 1079-1087)-based, Tang, Gnecco, and Geller (1989, Biometrika 76, 577-583)-based, and Westfall and Young 1989, Jour-nal of the American Statistical Association 84, 780-786)-based proce-dures are investigated and compared to standard techniques. Monte Carlo simulations for small to moderate sample sizes are performed give some recommendations for practical use.
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