I have 3 different DV that I try to model with 3 distinct models (linear mixed models) using the same set of IV. I found that the DV that I have the least amount of data for also has the lowest number of IV's in the final model, while the DV that has the largest amount of data has a larger number of remaining IV (including interactions). I tend to believe that this might be an artifact of data-availability. Might that be the case? And if so: Is that a serious problem when reporting these results in peer reviewed journal?
I know that many argue against stepwise reduction procedures, however my feeling is that (at least in my case) the selection mostly comes to the same final models irrespective of minor changes in the inital model. Are the constraints against model selection mostly valid in case of large numbers of IV or is it even in case of a relatively small number of initial IVs that there might be completely different results?