[R-sig-ME] GLMM - selection of models

[Ben Bolker]

There are strong theoretical arguments for **not** doing stepwise
selection on models (any kind, at all), e.g.
http://www.stata.com/support/faqs/statistics/stepwise-regression-problems/.
If you must, you can use `drop1()` to semi-automate the process, or
you can use MuMIn::dredge to do all-subsets fitting.

On Thu, Mar 16, 2017 at 5:15 PM, Marcos Monasterolo
<mmonasterolo at agro.uba.ar> wrote:
> Dear all. I am working with a GLMM in the lme4 package using 6 fixed
> factors and 1 random factor (plot). The syntax of my model is as follows:
>
>  M1 <- glmer(riquinsec~  adjacent field+ exph200+db500+exph500+db200+width+
> (1|plot), data = comuni1, family = poisson)
>
> I need to make a selection of models to get rid of non relevant variables,
> but the "step" function in lme4 is not appropriate for GLMM models.
> Which function can I use for a selection of models in GLMM?
>
> Thanks in advance for you kind help.
>
> ----
> Biól. Marcos Monasterolo
> Becario doctoral - Cátedra de Botánica General, Facultad de Agronomía, UBA
>
>         [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models