Re: [R] mixed-effects models with (g)lmer in R and model selection

Absolutely! Even more, consult a local expert in applying mixed effects models. The op's strategy sounded to me like a prescription to produce irreproducible results (due to over fitting). Cheers, Bert On Friday, February 19, 2016, Don McKenzie wrote: > This is a complicated and subtle stati

Re: [R] mixed-effects models with (g)lmer in R and model selection

Hello, Wilbert, You did give a good procedure for lme model selection! thanks! I learn some. I am also working on similar problem recently, maybe you can take a look at "glmmLasso" package, which allows model selection in generalized linear mixed effects models using the LASSO shrinkage method.

Re: [R] mixed-effects models with (g)lmer in R and model selection

This is a complicated and subtle statistical issue, not an R question, the latter being the purpose of this list. There are people on the list who could give you literate answers, to be sure, but a statistically oriented list would be a better match. e.g., http://stats.stackexchange.com/ >

[R] mixed-effects models with (g)lmer in R and model selection

Dear all, Mixed-effects models are wonderful for analyzing data, but it is always a hassle to find the best model, i.e. the model with the lowest AIC, especially when the number of predictor variables is large. Presently when trying to find the right model, I perform the following steps: 1.