I'm using SPSS and this drop-down menu:
Analyze -> General Linear Model -> Univariate.
DV: Number of times patient visited doctor over one year Factor 1: 2 levels: Two different drugs Factor 2: 2 levels: Gender Factor 3: 4 levels: Race Factor 4: 3 levels: drug taken morning, afternoon, evening Covariate: Age (continuous)
There are 500 subjects. Only 10 missing values, all in the factor with 4 levels.
The main effect I'm really interested in is for Factor 1. In a 1-way ANOVA it was highly significant. When I added the next 3 factors and the covariate in a full-factorial model it became not significant (none of the factors were, though when I had just 3 factors + the covariate 2 of the factors were significant).
- Have I included too many factors (+ the covariate) to expect a significant main effect for any of the factors? Somehow "overloaded" the model?
- When I tried a "custom" model, removing all the interactions from the model, 2 of the factors were now significant, which is what I expected. Is that legitimate?