I'm running hierarchical regression to determine whether or not a number of independent variables are able to explain a dependent variable. I have following models:
- Model 1: only controlvariables
- Model 2: Model 1 + independent variables
- Model 3: Model 2 + interaction term
When interpreting the significance of the different terms, should I only consider the last model or should I consider the model where I entered the terms. For instance, to investigate which controlvariables are significantly significant to the dependent variable, should I look at Model 1, and then, for the independent variables, consider Model 2? Or should I just look at the last model for the significance of the different terms?