[R] non positive-definite G matrix in mixed models: bootstrap?
Bruno L. Giordano
bruno.giordano at music.mcgill.ca
Tue Jul 11 15:31:29 CEST 2006
Dear list,
In a mixed model I selected I find a non positive definite random effects
variance-covariance matrix G, where some parameters are estimated close to
zero, and related confidence intervals are incredibly large.
Since simplification of the random portion is not an option, for both
interest in the parameters and significant increase in the model fit, I
would like to collect "unbiased" random effects estimates.
I used bootstrap to this purpose, creating a linear model for each cluster
and bootstraping the variance of the coefficients. Is this procedure
reasonable? Would it be reasonable in this case to keep the marginal portion
of the mixed model?
Note that in presence of positive-definite G matrix this bootstrap approach
and the mixed effect model give highly similar estimates and that in the non
positive-definite model the bootstrap and mixed model marginal-model
estimates are highly similar as well.
Thank you
Bruno
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