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gls for generalized linear model (ChenChun)
2 messages · ChenChun, Ben Bolker
ChenChun <talischen at ...> writes:
[snip]
* REML does nothing in glmer()--> So REML is not used in estimating the random effect for GLM? (Sorry I am new to mixed models)
Correct, see http://glmm.wikidot.com/faq#reml-glmm
* are you sure it makes sense to test the statistical significance of the random effect?--> My experiment is to estimate the survival of animals, which the survival experiment is conducted with a group of animals (ni) in the ith experiment, i.e. animals are clustered by expID. However, for some experiments, the animals are coming from the same basket. That's why basketID is also used as a random effect.
[snip]
The model output shows that the estimated variance between baskets is almost zero, indicating that maybe there is no basket effect, or it can be neglectable. What's why I would like to test whether including the random effect of basket significantly improves the model fitting. If not and the variance is small, I can leave out the basketID term. Do you think this is reasonable?
[snip] See http://glmm.wikidot.com/faq#random-sig ... Although opinions vary, I generally feel that one should leave random effects in the model as long as they are (1) suggested by the experimental design and (2) not messing up the model fit.