Sample size calculation for simulation-based multiple-testing procedures.
In this article, we present a simple method to calculate sample size and power for a simulation-based multiple testing procedure which gives a sharper critical value than the standard Bonferroni method. The method is especially useful when several highly correlated test statistics are involved in a multiple-testing procedure. The formula for sample size calculation will be useful in designing clinical trials with multiple endpoints or correlated outcomes. We illustrate our method with a quality-of-life study for patients with early stage prostate cancer. Our method can also be used for comparing multiple independent groups.
Bang
Heejung
H
Division of Biostatistics and Epidemiology, Department of Public Health, Weill Medical College of Cornell University, New York 10021, USA. heb2013@med.cornell.edu
Jung
Sin-Ho
SH
George
Stephen L
SL
D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D008297:Male; D015233:Models, Statistical; D011471:Prostatic Neoplasms / Q000628:therapy; D011788:Quality of Life; D012107:Research Design / Q000706:statistics & numerical data*; D018401:Sample Size; D016896:Treatment Outcome