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st: RE: RE: Covariates in ANOVAs


From   Miss Gina Micke <[email protected]>
To   "[email protected]" <[email protected]>
Subject   st: RE: RE: Covariates in ANOVAs
Date   Fri, 15 May 2009 04:30:46 +0000

Thanks for your input. Maybe I didn't make myself clear enough re "age range". Age range refers to actual age in days at each measurement. As all subjects were measured on the same day at each measurement event, the difference between subject ages is the same at each measurement event, so age at first measurement would be the data in the "age range" variable. Do you still think this should be inlcuded as a categorical variable?
________________________________________
From: [email protected] [[email protected]] on behalf of Joseph Coveney [[email protected]]
Sent: Friday, 15 May 2009 11:48 AM
To: [email protected]
Subject: st: RE: Covariates in ANOVAs

Miss Gina Micke wrote:

I would like to know how to control for an independent continuous variable when
using a repeated measures ANOVA. I have a 2x2 factorial design experiment with
males and females in each of the treatment groups (T1 & T2) measured at multiple
"events", each subject assigned an "id". The subjects are all different ages so
I would like to be able to control for the effect of "age range".

If I didn't have "age range" as a covariate my model would be as follows:

anova x T1 T2 sex T1*T2 T1*sex T2*sex T1*T2*sex/id|T1*event T2*event T1*T2*event
sex*event sex*T1*event sex*T2*event T1*T2*sex*event, repeated(event) partial
bse(id|T1*T2*sex)


Do I use the ANCOVA and cont(age range) command? Is this output the effects of
my fixed factors taking into account the effect of age range?

--------------------------------------------------------------------------------

First, the command line text shown doesn't look at all like correct syntax.
Second, by the name of it, a variable called "age range" would be categorical
and so you would not be using the -continuous()- option for it in -anova-.

Unless you have balanced data (equal representation of age ranges within each
factorial cell, as well as equal sex-by-treatment group cell sizes maintained
throughout the observation period), try something like the following to start
with:

xi3 i.treatment_group*i.age_group*i.sex*i.observation_interval
xtmixed response _I* || patient_id: , nolrtest variance reml

You'll need to install the user-written command, -xi3-, from SSC if you haven't
already.

Joseph Coveney



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