repeated measures anova, sphericity, epsilon, etc

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repeated measures anova, sphericity, epsilon, etc

 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, -- 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 [hidden email] http://gribblelab.org        [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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Re: repeated measures anova, sphericity, epsilon, etc

 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.pdfLast 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 ~~~~~~~~~~ - ([hidden email])              FAX: (+45) 35327907 ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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Re: repeated measures anova, sphericity, epsilon, etc

 > > 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 <[hidden email]>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 > ~~~~~~~~~~ - ([hidden email])              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 [hidden email] http://gribblelab.org        [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.