On Jun 4, 2013, at 4:46 PM, Kota Hattori wrote:
Dear all,
I have been searching ways to run power analysis for mixed-effects
models. However, I have not been successful
in the research. Today I would like to ask your help. As long as I
see from my search, Martin Julien wrote a package
called pamm for the power analysis. One of the limitations in the
current version is that pamm cannot handle
categorical fixed variables. Todd Jobes introduced his script to run
power analysis for mixed-effects models
(http://toddjobe.blogspot.co.nz/2009/09/power-analysis-for-mixed-effect-models.html
). However, some parts of
the script is beyond my knowledge. I am not sure if I can run power
analysis with categorical variables either. Is there
anybody who has run post hoc power analysis for mixed-effects
models? If you have experiences, I would like to
ask your help. Thank you very much for taking your time.
Can you provide a sensible justification for "post hoc power analysis?
I know the terminology has crept into widespread use due to its
existence in either SAS or SPSS (I forget which), but I have doubts
about its validity. It mixes up the order of statistical testing
logic. Power analysis is something done _before_ the study. If a
statistical procedure is done after a study's data is collected with
the very dubious assumption that the sample statistics are the
population statistics, it's not a power analysis.
--
David Winsemius, MD
Alameda, CA, USA
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