https://communities.sas.com/t5/SAS-Procedures/how-to-calculate-the-power-for-non-parametric-test-such-as/m-p/76558#M22206 Since the non-parametric tests do not depend on normality, I was wondering how to perfrom power analysis. any idea? thanks a lot! Thu, 22 Oct 2009 21:10:53 GMT Peggy 2009-10-22T21:10:53Z https://communities.sas.com/t5/SAS-Procedures/how-to-calculate-the-power-for-non-parametric-test-such-as/m-p/76558#M22206 Since the non-parametric tests do not depend on normality, I was wondering how to perfrom power analysis. any idea? thanks a lot! Thu, 22 Oct 2009 21:10:53 GMT https://communities.sas.com/t5/SAS-Procedures/how-to-calculate-the-power-for-non-parametric-test-such-as/m-p/76558#M22206 Peggy 2009-10-22T21:10:53Z https://communities.sas.com/t5/SAS-Procedures/how-to-calculate-the-power-for-non-parametric-test-such-as/m-p/76559#M22207 Just Google <BR /> kruskal wallis power<BR /> for lots of information on the power of the test.<BR /> <BR /> A fundamental part of a power analysis is 'against what' alternative. The Kruskal Wallis test has more power than an ANOVA if the alternative is not normal, but less if the alternative is normal. If you want to dig deeper, the "pitman relative efficiency" of the power comes to mind as a search term.<BR /> <BR /> As far as actually computing the power, you could use the large sample theory or do simulations for specific scenarios. Sun, 25 Oct 2009 15:20:42 GMT https://communities.sas.com/t5/SAS-Procedures/how-to-calculate-the-power-for-non-parametric-test-such-as/m-p/76559#M22207 Doc_Duke 2009-10-25T15:20:42Z