R help - Dec 2010 - Doing a mixed-ANOVA after accounting for a covariate

Dear r helpers,

I would like to look at the interaction between two two-level factors, one
between and one within participants, after accounting for any variance due
to practice (31 trials in each of two blocks) in the task.
It seems to require treating practice as a covariate.

All the examples I noticed for handling covariates (i.e. ANCOVA, including
the ones in Faraway's "Practical regression and anova using r")
use lm(),
but this doesn't handle repeated-measures.

I thought of a solution in the form of first running a regression on the
covariate:
> cov.accnt = lm (myMeasure ~ myCovMeasure, data=dat)
and then run the aov() on the residuals:
> m.aov = aov (cov.accnt$residuals ~ withinVar*betweenVar +
Error(subj/withinVar, data=dat)

Does it seem to be a valid answer to my problem?

Is there an existing function that can do this (perhaps more appropriately)?

Thank you for any help,
dror

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On Dec 26, 2010, at 7:42 AM, Dror D Lev wrote:
> Dear r helpers,
>
> I would like to look at the interaction between two two-level  
> factors, one
> between and one within participants, after accounting for any  
> variance due
> to practice (31 trials in each of two blocks) in the task.
> It seems to require treating practice as a covariate.
>
> All the examples I noticed for handling covariates (i.e. ANCOVA,  
> including
> the ones in Faraway's "Practical regression and anova using
r") use
> lm(),
> but this doesn't handle repeated-measures.
See if Dalgaard's piece in R-News offers better guidance:

http://www.r-project.org/doc/Rnews/Rnews_2007-2.pdf

>
> I thought of a solution in the form of first running a regression on  
> the
> covariate:
>> cov.accnt = lm (myMeasure ~ myCovMeasure, data=dat)
>
> and then run the aov() on the residuals:
>> m.aov = aov (cov.accnt$residuals ~ withinVar*betweenVar +
> Error(subj/withinVar, data=dat)
>
> Does it seem to be a valid answer to my problem?
>
> Is there an existing function that can do this (perhaps more  
> appropriately)?
>
> Thank you for any help,
> dror
-- 

David Winsemius, MD
West Hartford, CT

Dror,

Please look at the
demo(MMC.apple)
in the HH package

install.packages("HH") ## if you don't already have it.
library(HH)
demo(MMC.apple)

Please reply to the list if there are further queries.

Rich

On Sun, Dec 26, 2010 at 7:42 AM, Dror D Lev <dror.teach@gmail.com> wrote:
> Dear r helpers,
>
> I would like to look at the interaction between two two-level factors, one
> between and one within participants, after accounting for any variance due
> to practice (31 trials in each of two blocks) in the task.
> It seems to require treating practice as a covariate.
>
> All the examples I noticed for handling covariates (i.e. ANCOVA, including
> the ones in Faraway's "Practical regression and anova using
r") use lm(),
> but this doesn't handle repeated-measures.
>
> I thought of a solution in the form of first running a regression on the
> covariate:
> > cov.accnt = lm (myMeasure ~ myCovMeasure, data=dat)
>
> and then run the aov() on the residuals:
> > m.aov = aov (cov.accnt$residuals ~ withinVar*betweenVar +
> Error(subj/withinVar, data=dat)
>
> Does it seem to be a valid answer to my problem?
>
> Is there an existing function that can do this (perhaps more
> appropriately)?
>
> Thank you for any help,
> dror
>
>        [[alternative HTML version deleted]]
>
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> PLEASE do read the posting guide
>
http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
> and provide commented, minimal, self-contained, reproducible code.
>
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