Mixed Effects Model Power Calculations
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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