glmmPQL: random effects
This is a good question - surprised I haven't seen it before. The general answer to your question is that people don't generally worry about REML vs ML for generalized mixed models: http://bbolker.github.io/mixedmodels-misc/glmmFAQ.html#reml-for-glmms The proximal answer is that glmmPQL is a hybrid between lme and glm. When you specify a method= argument, glmmPQL tries to pass it to the glm function, which is expecting a function name. (i.e., "don't do this, it doesn't work")
On 18-01-25 09:09 AM, Cueva, Jorge wrote:
Hello everyone, I am working with glmmPQL because have data count (richness and number of individuals), in both cases have mean >5 and overdispersion. The literature says is necessary to distinct between ML (for random effects) and REML (fixed effects), but I got one error even with the nlme package active: Error in ML(x = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, : could not find function "ML" I am using: glmmPQL(Spp~1+Cattle+Equine+Mth.Prec,random = list(~1|Formation,~1|Cluster),data = VariabRLplot, family = "quasipoisson", method="ML") If I not use --method="ML"-- the model runs without warnings The questions are: 1. Can I distinct between "ML" and "REML" using glmmPQL? Or I must use some function like lme or lmer and later pass to glmmPQL 2. By other hand, with the random effects, "Cluster" is nested in "Formation", the syntax should be right, but I am not 100% sure. Thanks so much Jorge Cueva Ortiz Ing. Forestal ECU: 0993085161 GER: 0049 1631327886 [[alternative HTML version deleted]]
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