After much research I've listed a couple of ways to do repeated measures anova here:
http://gribblelab.org/2009/03/09/repeated-measures-anova-using-r/ including univariate and multivariate methods, post-hoc tests, sphericity test, etc. It appears to me that the most useful way is a multivariate model and then using Anova() from the car package. -Paul On Tue, Mar 3, 2009 at 5:37 PM, Paul Gribble <pgrib...@uwo.ca> wrote: > Have a look at >> >> http://cran.r-project.org/doc/Rnews/Rnews_2007-2.pdf >> > > Wow. I think my students would keel over. > > > Anova() from the car package looks promising - I will check it out. Thanks > > > > On Tue, Mar 3, 2009 at 4:00 PM, Peter Dalgaard > <p.dalga...@biostat.ku.dk>wrote: > >> Paul Gribble wrote: >> >>> I have 3 questions (below). >>> >>> Background: I am teaching an introductory statistics course in which we >>> are >>> covering (among other things) repeated measures anova. This time around >>> teaching it, we are using R for all of our computations. We are starting >>> by >>> covering the univariate approach to repeated measures anova. >>> >>> Doing a basic repeated measures anova (univariate approach) using aov() >>> seems straightforward (e.g.: >>> >>> +> myModel<-aov(myDV~myFactor+Error(Subjects/myFactor),data=myData) >>> +> summary(myModel) >>> >>> Where I am currently stuck is how best to deal with the issue of the >>> assumption of homogeneity of treatment differences (in other words, the >>> sphericity assumption) - both how to test it in R and how to compute >>> corrected df for the F-test if the assumption is violated. >>> >>> Back when I taught this course using SPSS it was relatively >>> straightforward >>> - we would look at Mauchly's test of sphericity - if it was significant, >>> then we would use one of the corrected F-tests (e.g. Greenhouse-Geisser >>> or >>> Huynh-Feldt) that were spat out automagically by SPSS. >>> >>> I gather from searching the r-help archives, searching google, and >>> searching >>> through various books on R, that the only way of using mauchly.test() in >>> R >>> is on a multivariate model object (e.g. mauchly.test cannot handle an >>> aov() >>> object). >>> >>> Question 1: how do you (if you do so), test for sphericity in a repeated >>> measures anova using R, when using aov()? (or do you test the sphericity >>> assumption using a different method)? >>> >>> Question 2: Can someone point me to an example (on the web, in a book, >>> wherever) showing how to perform a repeated measures anova using the >>> multivariate approach in R? >>> >>> Question 3: Are there any existing R functions for calculating adjusted >>> df >>> for Greenhouse-Geisser, Huynh-Feldt (or calculating epsilon), or is it up >>> to >>> me to write my own function? >>> >>> Thanks in advance for any suggestions, >>> >> >> Have a look at >> >> http://cran.r-project.org/doc/Rnews/Rnews_2007-2.pdf >> >> Last time this came up, John Fox also pointed to some of his stuff, see >> http://finzi.psych.upenn.edu/R/Rhelp08/archive/151282.html >> >> -- >> O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B >> c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K >> (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 >> ~~~~~~~~~~ - (p.dalga...@biostat.ku.dk) FAX: (+45) 35327907 >> > > > > -- > Paul L. Gribble, Ph.D. > Associate Professor > Dept. Psychology > The University of Western Ontario > London, Ontario > Canada N6A 5C2 > Tel. +1 519 661 2111 x82237 > Fax. +1 519 661 3961 > pgrib...@uwo.ca > http://gribblelab.org > -- Paul L. Gribble, Ph.D. Associate Professor Dept. Psychology The University of Western Ontario London, Ontario Canada N6A 5C2 Tel. +1 519 661 2111 x82237 Fax. +1 519 661 3961 pgrib...@uwo.ca http://gribblelab.org [[alternative HTML version deleted]]
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