[R] help with unequal variances

B77S bps0002 at auburn.edu
Tue Nov 1 20:39:04 CET 2011


the following is a more appropriate forum for your question, seeing as this
has nothing to do with R (per se). 

http://stats.stackexchange.com/questions

good luck.




peak99 wrote:
> 
> Hello,
> 
> I have some patient data for my masters thesis with three groups (n=16, 19
> & 20)
> 
> I have completed compiling the results of 7 tests, for which one of these
> tests the variances are unequal.
> 
> 
> I wish to perform an ANOVA between the three groups but for the one test
> with unequal variance (<0.001 by both bartlett and levene's test) I am not
> sure what to do.
> 
> I thought i would run ANOVA with bonferonni post-test for groups with
> equal variances, then for the test with unequal variance i would use the
> welch correction and games-howell post-test.  Does this sound reasonable?
> 
> Someone has also recommended to me to use Kruskal-wallis ANOVA, then use
> Wilcoxon sign rank test pairwise to determine which groups are
> significantly different (ON ALL DATA, both equal and unequal variance
> tests).  I don't think this is right, for two reasons:
> 
> 1) Kruskal-wallis is for non-gaussian data, and i have no reason to
> believe they are not normal.
>     - I have run normality tests which say they are normal, although
> perhaps my sample sizes are too small for a normality test?
> 2) i believe running pairwise Wilcoxon sign rank test is not acceptable
> unless there is a post-test correction for multiple comparisons (i am not
> aware of one); also on the wiki page for this test one of the assumptions
> says "Under the null hypothesis the distributions of both groups are
> equal" which i read to say that the variances must be equal.
> 
> So I think there recommendations were based more on sample size and
> normality, and not my issue with variance?
> 
> 
> Ultimately i would like to know if i am going about this right with my
> deduction (ANOVA/Bonferonni of the test results, but welch correction and
> games-howell for the test with significantly different variances).  and if
> not why and/or what you think is a better option.
> 
> most appreciated to any help received!
> 


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