[R-sig-ME] model selection methodology

[Alessandra Bielli]

Dear List,

I am writing this here because I am using glmmTMB to run a zero inflated
model, but the question is possibly more general, so please feel free to
redirect me to another list/help page.

I want to test whether a treatment (a) has an effect on a
dependent variable (y), so I built a full model :

m1 <- glmmTMB(y ~ a + offset(log(b)) + (1|ID), data=x, ziformula =  ~ a,
              family="poisson")

I used the dredge function to generate a model selection table and the top
model did not include the treatment (a) in the conditional model nor in the
ZI model.

My usual way to proceed is to run diagnostics for the selected model and
conclude that the effect of treatment on my dependent variable is not
statistically significant.

My questions are:
1- is this the right way to proceed or should I check the diagnostics plots
BEFORE model selection?
2- it has happened to me that, while the full model converged, the reduced
model gave a convergence warning message. Considering that my only goal was
to test whether the effect of treatment was significant or not, how would
the convergence issue influence my conclusions?

I feel like these are very basic questions but very important because I do
not want to draw wrong conclusions. Thanks,

Alessandra

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