|Date: ||Wed, 21 Feb 2001 14:02:59 -0000|
|Reply-To: ||"Manktelow, B." <bm18@LEICESTER.AC.UK>|
|Sender: ||"SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>|
|From: ||"Manktelow, B." <bm18@LEICESTER.AC.UK>|
|Subject: ||Re: multiple comparisons of not normally distributed data|
|Content-Type: ||text/plain; charset="iso-8859-1"|
Another alternative would be to use PROC NPAR1WAY to perform a
Kruskal-Wallis test on all three groups for each outcome. Then only perform
pairwise tests when the K-W test reaches statistical significance (5% ?).
This all assumes that it is not possible to apply transformations to the
original data to approximate Normal distributions and homoscedasticity and
then apply ANOVA/GLM.
Either way I feel it is better to report all of you findings and let others
interpret them in the light of you analysis (don't just report the
statistically significant ones).
From: Christian F.G. Schendera [mailto:schendera@NIKOCITY.DE]
Sent: 21 February 2001 10:26
Subject: multiple comparisons of not normally distributed data
Data situation: 3 independent groups, several continuous dependent/response
vars. Continuous vars are not normal distributed (only a third of the data
reach ShapiroWilks >0.1).
Problem: Collegues compared the three groups pairwise with simple Mann
Whitneys at alpha 0.05. Journal reviewers criticized this proceeding for not
having used p-adjusting procedures like Bonferroni.
Question: Are reviewers right? How could one apply p-adjusting procedures
when conditions for ANOVA/GLM are not met? Could MULTTEST be used to perform
multiple comparisons on the described data? Or adjust the p in the pairwise
comparisons? Whta would you recommend in this situation?
Thanks in advance,