On Nov 3, 2011, at 3:47 AM, David A. wrote: > > Hi, > > I am trying to estimate the sample size needed for the comparison of two > groups on a certain measurement, given some previous data at hand. I find > that the data collected does not follow a normal distribution, so I would > like to use a non-parametric option for sample size calculation. > > I found the pwr package but I don't think it has this option and on the > internet found that http://www.epibiostat.ucsf.edu/biostat/sampsize.html says > only PASS allows non-parametric sample size calculations (although the > webpage is not updated). > > Any help would be greatly appreciated > > Thanks, > > Dave
The first question is how "non normal" are your data? If you used some formal test for normality and the p value was <=0.05, I would suggest that you search the R-Help archives for a plethora of discussions on testing for normality. You will find that such tests should largely not be used in deference to the question "Are the data normal enough?". If they are or can be transformed reasonably, use standard functions for calculating power and sample size, such as power.t.test(). If you need to use a non-parametric test, you might want to review this page by Jerry Dallal: http://www.jerrydallal.com/LHSP/npar.htm which has some general guidelines for calculating sample size predicated upon using standard parametric tests and then adjusting the sample size using the ARE (asymptotic relative efficiency) based upon the non-parametric intended. HTH, Marc Schwartz ______________________________________________ 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.
