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Message: 3
Date: Fri, 25 Feb 2011 20:58:13 -0500
From: "Nichols, Krista M" <kmnichol at purdue.edu>
To: "r-sig-ecology at r-project.org" <r-sig-ecology at r-project.org>
Subject: [R-sig-eco] MCMCglmm and power analysis
Message-ID:
<8B3D151076714145AE9D54B657B3C118D67696F499 at VPEXCH06.purdue.lcl>
Content-Type: text/plain
Hi All,
I have a question about using MCMCglmm with simulated data for a power
analysis of heritability. I'm specifically using MCMCglmm and another
package called PEDANTICS to simulate phenotypes across a pedigree; the
response data are binomial. I need to calculate power over these
simulated data sets, but am having a hard time grasping how to do this in
a Bayesian analysis. I understand that I can compare models in MCMCglmm
with the DIC, but as far as I know, there is no formal way to test
whether there is a 'significant difference' between two models with the
DIC that would be analogous, say, to a likelihood ratio test in a normal
linear mixed model. Does anyone know that this is indeed true (i.e.
whether the DIC has statistical properties that would allow formal
testing for significance so that I could use this for a power analysis),
or if there is some other way to determine the significance in comparing
models for such a power analysis? Note that I'm specifically interes!
ted in testing the 'significance' of a random effect (animal ID from a
pedigree analysis), so looking for overlap with zero using HPDinterval
will not work, as random effects are constrained to be greater than zero
in MCMCglmm.
Any help, thoughts on this will be greatly appreciated!
Thanks,
Krista
Krista M. Nichols
Associate Professor
Purdue University
Departments of Biological Sciences & Forestry and Natural Resources
915 W State Street
West Lafayette, IN 47907
765.496.6848 (w)
765.494.0876 (f)
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