[R-sig-ME] variance components models with zero estimates
David Airey
david.airey at vanderbilt.edu
Sun Jun 8 02:23:24 CEST 2008
When a variance components mixed model is run in Stata, if some of the
variance components are zero, the model may not converge, for rational
reasons according to the manual entry. However, when the same model is
run in SAS, the models with variance components that estimate to zero
nonetheless converge. According to some SAS user friends, this is
normal SAS behavior (I'm new to SAS as of yesterday). If I'm
interested in looping through a set of such models, the SAS behavior
is preferred. However, in Stata such models can be formulated as
multilevel models that can dramatically reduce the dimension of the
design matrix. The context where both behaviors is important is mixed
models for gene set enrichment analysis, where there is a possibility
of hundreds of models.
Does R lme4 handle variance components mixed models that have
estimates of zero for some of the variance components like SAS or
Stata? Is it possible to loop through variance components models when
some of the variance components are zero? What is a suggested
procedure for doing so in R? In Stata, I would probably use an EM only
guess at which variance components were substantive, and then fit one
of several models. What about R lme?
Cheers,
-Dave
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