[R-sig-ME] Generalized Linear Models

[Agnes Schneider]

Hi,

I'm carrying out an analysis on future time expressions in English on the basis of a corpora of spoken language. I am using a linear mixed effects model (glmer) because when I coded the data I realized that there is considerable variability within each conversation concerning the choice of future markers. So I have a model consisting of a categorical dependent variable (Future time marker WILL or BE GOING TO), a number of fixed effects (syntactic, semantic and extralinguistic variables), an a random effect which is File. Not all of my independent variables show a significant effect on the choice of future marker. My questions now are:

1. Is the procedure at arriving at a minimal adequate model the same as for logistic regression models (glm)?
2. How do I find out whether there is reason to assume overdispersion?
3. How do I find out whether my models (both the initial and the final model) have predictive power?
4. How do I determine whether interspeaker variability (File) is stronger than the fixed effects?

I am grateful for any comment on my questions!!
Thanks
Agnes