re:st: Repeated Measures ANOVA vs. Friedman test

["Airey, David C" <david.airey@vanderbilt.edu>]

.

With small samples, it is hard to evaluate assumptions, as you pointed out. That is why someone might choose to be conservative and use a nonparametric method. If your data really did come from normal distributions, and sphericity was met, you could reliably use the RM ANOVA with very few observations. Regardless of which method, power will be low. Run both and hope your conclusion doesn't depend on the method. If it did that would just probably tell you to get more data, i.e., proceed with the experiment.

-Dave


> Hi All,
> 
> I was going to compare some data from a pilot study where there were
> repeated measures taken from subjects (1 measurement each at baseline,
> 2 weeks and 4 weeks).  I've got a small sample size (n=6 per group)
> and the outcome of interest is a continuous variable.  My question is
> whether I can use a repeated measures ANOVA to evaluate such a small
> sample size or whether I should go with Friedman?  Or should I use
> something else - a mixed model perhaps?
> 
> I did draw histograms and box plots to see what the distributions and
> it looks more or less normally distributed but it's hard to really say
> with such a small sample size.  Additionally, the sktest had a value
> >0.05.  So is it okay to use RM ANOVA for n of 6 per group?
> 
> Thanks in advance for any help with this.


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