re: Re: st: post test comparisons of means using repeated measures.

[Richard Williams <Richard.A.Williams.5@nd.edu>]

At 09:31 AM 1/6/2004 -0600, David Airey wrote:
> Joseph Coveney said,
>
> > I've tried to compare both approaches in the do-file below using the dataset
> > that Alan cited.  The -mtest(bonferroni)- approach yields far more null
> > hypothesis rejections than the corresponding Bonferroni-adjusted separate
> > t-test approach.  Such a discrepancy is surprising.
> This happens in a oneway between-subjects design too. The reason the 
> contrast is more powerful than the independent ttest is that the contrast 
> uses information for MSw from all groups and is therefore more accurate. 
> Of course this is true only if the homogeneity of variances assumption 
> holds. Perhaps along the same vein, the contrasts reject the null more 
> than the dependent ttests because more information is used for the 
> estimate of error, and in this case homogeneity of differences variances 
> holds? The dependent ttest is sometimes preferred because you can use 
> information from only those means tested, which is useful when sphericity 
> is violated.
I just tried this with a oneway problem, and get the same kinds of results: 
The -mtest(bonferroni)- approach yields more null hypothesis rejections 
than the corresponding Bonferroni-adjusted separate t-test approach.  These 
adjustments are already awfully conservative, and choosing an approach that 
makes them even more so is not very appealing!  Although I guess you have 
to do what is right.  I would think, though, that you would avoid the 
separate t-test approach unless it is clearly necessary, e.g. only go this 
route if homogeneity of variances does not hold?

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