Message-ID: <60A5728A-3228-4AB1-A2FA-2465FF6FD40A@comcast.net>
Date: 2010-12-26T13:59:35Z
From: David Winsemius
Subject: Doing a mixed-ANOVA after accounting for a covariate
In-Reply-To: <AANLkTim1MtfLfaJ0CZZGdBo-Gu=mekcrYZKe+_MuE436@mail.gmail.com>
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