Message-ID: <1260721763575-963016.post@n4.nabble.com>
Date: 2009-12-13T16:29:23Z
From: protonringe
Subject: Repeated Measures Analysis - GLM
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.