generalized linear mixed models with a beta distribution
Jeff Evans-5 wrote:
lme4 does have a leg up on GLIMMIX in other areas, though. The latest SAS release (9.2) is now able to compute the Laplace approximation of the likelihood, but it will only fit an overdispersion parameter using pseudo-likelihoods which can't be used for model selection. I'm not sure what lme4 is doing differently through the quasi-distributions that allows this, but it's enormously useful. Jeff
Sorry, but I wouldn't necessarily take comfort from this. I must confess that I can't keep the distinctions between marginal pseudo/quasi-likelihoods in my head, but on what grounds are you confident that the number that lme4 produces can be used for model selection? (I would guess that) Some people would be happy using QAIC based on pseudo-likelihoods, some people wouldn't be happy with anything other than a true likelihood (or approximation thereof). This discussion is probably better for r-sig-mixed-models ... Ben Bolker
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