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Re: st: Non-normal alternative to MANOVA


From   marietherese.kelly@flinders.edu.au
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Non-normal alternative to MANOVA
Date   Sat, 3 Jul 2010 20:03:17 +0930

Thanks for the replies.
I've had a look at transforming the data or using lnskew0, the problem is there
are 15 variables, each measured at 3 times periods (baseline, 7 weeks and 3
mothns after treatment) and it's pretty difficult to find a transformation that
works for all of them. The data were skewed at baseline and it only got worse
after treatment. The confounder numint (number of interventions) is a major
issue so I can't ignore it. With 3 repeated measurements I wasn't sure if you
could use lnskew0 separately on all 3 of them if I'm interested in changes from
baseline?

I'll have a look at ranking the data - is there a good reference anywhere on how
to do that? I did it once in the past but can't remember the details.

> Hi all,
> I have been asked to analyse a small dataset from a randomized controlled
trial,
> with 24 subjects (12 in each group, control and intervention). There are 3
sets
> of continuous outcome measures (b1, b2, b3) taken at baseline, 7 weeks and 3
> months, and 2 variables  which need to be controlled for  - level of
impairment
> impair (binary) and number of interventions numint (continuous integer).
>
> If the data were normal I would have done something like this:
>
> manova b1 b2 b3=group impair numint, continuous(numint)
>
> and then do various manova tests.
>
> Unfortunately the outcome data b1-3 are highly skewed, so I can't use manova.
> What would be a good alternative?
>
> Thanks.
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