R help - Mar 2010 - how to analyze repeated measures count data?

Dear R community,

I've data-set with reaction times and count data (answers - yes, no)  
of N subjects under conditions A, B.
For the analysis reaction time I used aov.

fit.rt = aov(rt ~ A * B + Error(subjects/(A*B)), data = m )

But how do I analyze the frequencies correctly?

example fable of frequencies from one subject:

, , = A1

       	B1 	B2 	B3
   yes   31     36    19
   no    22     27    10
, ,  = A2

       B1       B2    B3
   yes   22     27    10
   no    31     36    19

Is a generalized linear model the right method?
How do I specify the same model for the count data (frequencies) in glm?

is this right: glm(count~A*B*answer+(1|subject),family=poisson)?

Regards, Ren?

Not glm, it should be glmer in lme4 package.

Ronggui

On 22 March 2010 22:31, Ren? Mayer <mayer at psychologie.tu-dresden.de>
wrote:
> Dear R community,
>
> I've data-set with reaction times and count data (answers - yes, no) of
N
> subjects under conditions A, B.
> For the analysis reaction time I used aov.
>
> fit.rt = aov(rt ~ A * B + Error(subjects/(A*B)), data = m )
>
> But how do I analyze the frequencies correctly?
>
> example fable of frequencies from one subject:
>
> , , = A1
>
> ? ? ? ?B1 ? ? ?B2 ? ? ?B3
> ?yes ? 31 ? ? 36 ? ?19
> ?no ? ?22 ? ? 27 ? ?10
> , , ?= A2
>
> ? ? ?B1 ? ? ? B2 ? ?B3
> ?yes ? 22 ? ? 27 ? ?10
> ?no ? ?31 ? ? 36 ? ?19
>
> Is a generalized linear model the right method?
> How do I specify the same model for the count data (frequencies) in glm?
>
> is this right: glm(count~A*B*answer+(1|subject),family=poisson)?
>
> Regards, Ren?
>
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>


-- 
Wincent Ronggui HUANG
Doctoral Candidate
Dept of Public and Social Administration
City University of Hong Kong
http://asrr.r-forge.r-project.org/rghuang.html