My dependent variable is not normally distributed. I chose the Gamma log link, and I hope this is correct. I wasn't entirely sure with this because the dependent variable is actually a whole lot of percentages. I know this isn't technically continuous, but if I choose Poisson, it excludes most of my data. so question 1. if this is the wrong distribution, what is going wrong with the others?
Next, when I run the model, I have a few factors which are sex, stage (5 categories) and number of offspring (1 or 2 only). My covariates are weight and the other dependent variable, which are blood cell counts. I then selected all of these for the model, with an interaction between sex and stage, sex stage and offspring, sex and offspring. I have also played around by taking these in and out, and not having interactions at all. However, I have done single analysis on this before, and am interested in sex and stage related to my dependent variable. I also checked the box for pairwise comparisons, and Bonferroni.
So these are the questions I have:
1) if my interactions are either approaching significance or not significant, can I still look at the pairwise Bonferroni figures and quote the significant values from that?
2) If I take all my interactions out, but want to look at how my dependent variable is affected by stage in females only, can I exclude male cases, and run two separate models (then exclude females). If I explain this in a paper, saying that I ran three different (looking at the original also) models and use the results for all, is this valid? Or would this open up the possibility of errors.
3) I have been told by one person that if I have an interaction (significant or not), I can no longer look at the single effects. Is this true?
4) If my interaction between sex/stage and my dependent variable is not significant, should I exclude it from the model? The AIC doesn't change very much between them. If I am allowed to do 1 from above, there are a couple of interesting things happening.
5) why are my tests of model effects always significant but my parameter estimates aren't? is it because of the various levels in some of my factors?