On 09/27/2010 08:09 PM, Paul Miller wrote: > Hello Everyone, > > I'm trying to conduct a couple of power analyses and was hoping > someone might be able to help. I want to estimate the sample size > that would be necessary to adequately power a couple of > non-inferiority tests. The first would be a log-rank test and the > second would be a Wilcoxon rank-sum test. I want to be able to > determine the sample size that would be necessary to test for a 3 day > difference in median recovery time between 2 groups of cancer > patients. > > Both of these tests are infeasible using SAS Proc Power and I haven't > been able to find information about how to do them using either SAS > or R. > > Does anyone know how to perform either of these calculations? If so, > I'd greatly appreciate it if you could share a couple of examples.
I don't think it is possible in general. You need to put up some assumptions about the shape of the distributions. It is a generic problem with nonparametric tests that they are only nonparametric under the null hypothesis (so to speak). I.e., the null distribution of the test statistic does not depend on the distribution, but as soon as you get to matters of efficiency and power, it begins to matter what the distribution and the alternative hypothesis is. -- Peter Dalgaard Center for Statistics, Copenhagen Business School Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
