[R] Mixed Effects Model Power Calculations

[Dimitris Rizopoulos]

I don't know what specific application Rick has in mind, but if there 
is possibility of missing values (which is common, e.g., in 
longitudinal studies) then this should also be taken into account in 
the power calculations.

Best,
Dimitris

----
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven

Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/16/336899
Fax: +32/16/337015
Web: http://www.med.kuleuven.be/biostat/
     http://www.student.kuleuven.be/~m0390867/dimitris.htm


----- Original Message ----- 
From: "Henric Nilsson" <henric.nilsson at statisticon.se>
To: <rab45+ at pitt.edu>
Cc: <r-help at stat.math.ethz.ch>
Sent: Wednesday, August 17, 2005 10:42 AM
Subject: Re: [R] Mixed Effects Model Power Calculations


>
> On Ti, 2005-08-16, 21:17, rab45+ at pitt.edu skrev:
>
>> Is there an R package available that would facilitate doing a 
>> power/sample
>> size analysis for linear mixed effects models?
>
> I'm not aware of such a package (others might be...).
>
> When it comes to sample size calculations, especially for tricky 
> designs
> and/or advanced methodology, simulation is usually the best 
> approach. An
> example using `lme' can be found at
>
> http://maven.smith.edu/~nhorton/R/
>
>
> HTH,
> Henric
>
>> I have seen the Java applets made available by Russell Length which 
>> would
>> seem to be able to handle most any lme, but there is little 
>> documentation
>> and it's not clear how the models need to be formulated.
>>
>> Rick B.
>>
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