Model building, p value of GLM for whole model?

I have three GLM models (poisson distribution) that each have different factors but the same response variable. I plan to compare the fit of the models using AIC, but first I want to see if any of the models are significant according to a p value. Is is possible to get a p value for a whole model w/glm? Each model has 1 significant factor and one or two non-significant factors, but I was told to leave these non-significant factors in the models instead of removing them with sinful backwards stepwise regression.

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 What software are you using? – Peter Flom Oct 3 '12 at 17:05 You must subscribe to Frank Harrell's philosophy and arguments if you think stepwise regression is sinful! – Michael Chernick Oct 3 '12 at 17:19 I'm using R. I just learned about the sins of stepwise regression....my original analysis and two stats classes were pro-stepwise – Jo Lewis Oct 3 '12 at 17:25

You might also consider evaluating each model using $R^2$ and each model's predictive accuracy in cross-validation. For the latter, it's helpful to use the same cross-validation "folds" with each of your models.