Hello to the R world... I have some problems regarding a GLM - repeated measures analysis.
I want to test overall differences between AgeClass and Treatment (between subject) with OpenR1+OpenR2+OpenR3 (repeated measures, within subject). The table looks kind like this: AgeClass Treatment OpenR1 OpenR2 OpenR3 1 1 0 0 12.63 1 1 12.67 3.83 45.67 1 1 38.46 65.38 75.21 1 1 14.46 0 17.96 1 2 27.83 47.33 66.38 1 2 15.75 0 10.21 1 2 43.96 41.04 51.88 1 2 52.96 55.54 41.58 1 3 43.13 71.25 82.71 1 3 0.25 18.46 27.04 1 3 0.79 21.75 68.38 2 1 0 0 0 2 1 0 0 0 2 1 1.17 18.75 45.67 2 1 0 0 0 2 1 0 0 49.42 2 2 2.13 0 26.63 2 2 0 8.13 23.88 2 2 2.25 0 0 2 2 30.96 25.71 10.92 2 3 33.33 30.71 16.63 2 3 0 20.04 14.88 2 3 24.96 0 3.88 . . . I tried several things, for example this: aov(?????~(OpenR1*OpenR2*OpenR3*AgeClass*Treatment)+Error(??????/(OpenR1*OpenR2*OpenR3))+(AgeClass*Treatment)) I don't really know what response-variable to use, or what the subject-variable is.... There is no problem to create the model with SPSS, but for my Diploma-Thesis in biology i want to do all the statistics with R... Regards and many thanks in advance.... Ingo -- View this message in context: http://n4.nabble.com/Repeated-Measures-Analysis-GLM-tp963016p963016.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
