Hi I'm having difficulty working out how to get what I think is the appropriate partitioning of variability in a repeated measures setup. I have G=5 treatment-groups, each containing n=6 subjects, and a response is measured on each subject on t=4 occasions. I think the anova degrees of freedom should partition as follows - Between-subjects: G*n-1=29 [ between-groups: g-1 = 4 , between-subjects residual G*(n-1) = 25 ] Within-subjects: G*n*(t-1)=90 [ between-occasions t-1=3 , occasion:group interaction (G-1)*(t-1) = 12 , within-subject residual G*(n-1)*(t-1)=75 ] What's the best way to tackle this analysis in R * ? Hope you can help cheers Bob Kinley *[ R 2.15.2 , windows xp ] [[alternative HTML version deleted]]
Hi I'm having difficulty working out how to get what I think is the appropriate partitioning of variability in a repeated measures setup. I have G=5 treatment-groups, each containing n=6 subjects, and a response is measured on each subject on t=4 occasions. I think the anova degrees of freedom should partition as follows - Between-subjects: G*n-1=29 [ between-groups: g-1 = 4 , between-subjects residual G*(n-1) = 25 ] Within-subjects: G*n*(t-1)=90 [ between-occasions t-1=3 , occasion:group interaction (G-1)*(t-1) = 12 , within-subject residual G*(n-1)*(t-1)=75 ] What's the best way to tackle this analysis in R * ? Hope you can help cheers Bob Kinley *[ R 2.15.2 , windows xp ]
1. Please do not multiple post. 2. One approach would be mixed effects models. See the nlme and lme4 packages. 3. But there are a host of others (including, perhaps, just ?aov.). 4. This is a statistical question, and off topic here. Post on the r-sig-mixed-effects models list instead or s statistical list like stats.stackexchange.com. -- Bert On Mon, Feb 18, 2013 at 2:38 AM, Robert D Kinley <rdkinley at gmail.com> wrote:> Hi > > I'm having difficulty working out how to get what I think is the > appropriate partitioning of variability in a repeated measures setup. > > I have G=5 treatment-groups, each containing n=6 subjects, and a response > is measured on each subject on t=4 occasions. > > I think the anova degrees of freedom should partition as follows - > > Between-subjects: G*n-1=29 > > [ between-groups: g-1 = 4 , > > between-subjects residual G*(n-1) = 25 ] > > Within-subjects: G*n*(t-1)=90 > > [ between-occasions t-1=3 , > > occasion:group interaction (G-1)*(t-1) = 12 , > > within-subject residual G*(n-1)*(t-1)=75 ] > > What's the best way to tackle this analysis in R * ? > > Hope you can help > > cheers Bob Kinley > *[ R 2.15.2 , windows xp ] > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at 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.-- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm
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