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RE: st: Unbalanced repeated measures analysis question


From   "Ploutz-Snyder, Robert (JSC-SK)[USRA]" <robert.ploutz-snyder-1@nasa.gov>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Unbalanced repeated measures analysis question
Date   Wed, 21 Jul 2010 16:37:24 -0500

Karin,
I feel your pain RE Stata's anova syntax for repeated measures...  But I also agree with David that I think your better bet is probably to use -xtmixed- and then apply -margins- for  your post-hoc comparisons, given the imbalance issue.  You can use -margins- to compare each of the three measures to the gold standard--akin to simple effect contrasts.

If you wish to remain in the anova syntax, you might want to check out the user written -anovalator- command, thanks to Phil Ender from UCLA.  But from the sounds of your imbalanced design, I would tend to lean more to -xtmixed- with -margins-

(BTW--the Phil's website at UCLA has some nice walk-throughs of all of this.)

Rob

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Airey, David C
Sent: Wednesday, July 21, 2010 4:07 PM
To: statalist@hsphsun2.harvard.edu
Subject: re: st: Unbalanced repeated measures analysis question

.

I think when you have comparisons to a gold standard, or all comparisons with one control, that there are specific ANOVA post-hoc tests that perform better than all possible or all pairwise comparisons procedures.

There is the complication that you are testing for equivalence, as you say.

The Stata command -xtmixed- can do what -anova- can. Sometimes -manova- or -mvtest- is useful with repeated measures too.

It is hard to understand how your design is unbalanced without seeing the data cross-tabs, etc.



> Hi
> 
> I have data on measuring a biological property for three different
> methods plus a gold standard. Different people were trained in each
> method (1,2 or 3) and measured the same subjects during different
> sessions, together with the gold standard measurement.
> 
> So the data look like
> SubjectID MeasurerID MeasurerType Result GoldStandard  Diff
> 1         1          1            95     99            -4
> 1         2          3            102    99            +3
> 1         3          2            92     99            -7
> ...
> 1        10          3            105    99            +6
> 2         1          3             98   100            -2
> ...
> 
> Sometimes patients would be called in to see the consultant and so
> missed for a particular measurer, but otherwise all the measurers
> would measure all the patients seen in a particular session. Different
> sets of measurers (but all trained by methods 1,2 or 3) were used on
> each session (individual measurers 1-10 on session 1, 11-20 on session
> 2 etc).
> 
> The gold standard measurements on each session are roughly normally
> distributed, as are the differences from the gold standard. We are
> interested in the accuracy of each of the three methods.
> 
> Is it OK to do some sort of repeated measures ANOVA here, with an
> unbalanced design? If it is what would be the syntax (Stata 10)? Sorry
> to sound pathetic but I just can't get the anova command with the
> repeated option to work here.
> 
> Is there a better measure to use than the difference to reflect the
> fact that we are interested in a comparison with a gold standard?
> 
> Thankyou
> Karin

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