Thank you David, for the reference to Dalgaard's paper in Rnews_2007-2. Unfortunately I don't seem to have the mathematical-statistical sophistication required to adapt the example in Dalgaard's paper for my case.
I hope someone can suggest a less-mathematical direction for solution. Thanks again, dror ---------------------------- On Sun, Dec 26, 2010 at 3:59 PM, David Winsemius <dwinsem...@comcast.net>wrote: > > 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 > > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
