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non-parametric sample size calculation

2 messages · David Winsemius, Marc Schwartz

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On Nov 3, 2011, at 3:47 AM, David A. wrote:

            
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