I've never heard about using "permutations to assess the p-value."
Would you mind elaborating on this a bit with a very simple, concrete
example? If you don't have the time, would you mind sharing a
reference or two on the rationale and how to do this?
Thanks!
Ryan
On Jun 29, 11:19 am, "BXC (Bendix Carstensen)" <b...@steno.dk> wrote:
> Use regression with baseline as covariate and treatment as factor to estimate the effect, but use permutations to assess the p-value --- you can acually enumerate all of the possible treatment allocations: 15 choose 7 is only 6435.
> Best regards,
> Bendix
> > -----Original Message-----
> > From: MedStats@googlegroups.com
> > [mailto:MedStats@googlegroups.com] On Behalf Of Christian Lerch
> > Sent: 29. juni 2009 19:32
> > To: MedStats
> > Subject: {MEDSTATS} parametric/non-parametric, change from
> > baseline, covariates
> > I've been asked to look over a statistical analysis. At the
> > moment, Mann-Whitney-U-Test and Wilcoxon signed-rank test were used.
> > It's a tiny RCT (n1=7, n2=8 participants) in which both the
> > comparison of before and after values for each group and the
> > comparison of both groups at the end of the study are of
> > interest. Ideally, both analyses should be based on 'change
> > from baseline'.
> > RCTs in this field (with a reasonable sample size) are
> > generally analysed by ANCOVA (using before values as
> > covariate , based on 'change from baseline').
> > Any suggestion?
> > Regards,
> > Christian- Hide quoted text -
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