R help - Dec 2009 - 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


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Dear Ingo,

One approach would be to use the Anova() function in the car package. See
?Anova and in particular the O'Brien and Kaiser example, which is for a more
complicated repeated-measures design. If you want to get "type-III"
tests
(as opposed to the default "type-II" tests), be careful with the
contrast
coding for the between-subjects factors.

I hope this helps,
 John

--------------------------------
John Fox
Senator William McMaster 
  Professor of Social Statistics
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
web: socserv.mcmaster.ca/jfox

> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at
r-project.org]
On
> Behalf Of protonringe
> Sent: December-13-09 11:29 AM
> To: r-help at r-project.org
> Subject: [R] 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*Ope
n
> R2*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.
> 
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