Interpretating hierarchical regression results

I’m needing a little bit of direction in understand my first hierarchical multiple regression data.
My research question is to what extent does alcohol explain the association between negative mood and impulsivity in academic performance (DV).
I’ve ran the analysis - at the first stage of the model when I only include impulsivity and negative mood - negative mood isn’t significant. When I introduced alcohol use (mediating variable) into the second stage negative mood still wasn’t significant. However, prior to the analysis when I ran correlations negative mood was significant related to the DV - academic performance.
How would you interpret this? It’s my first time doing this analysis and I’m just not sure how to interpret it. Any help would be appreciated.


Less is more. Stay pure. Stay poor.
Hierarchical term gets used in different ways. You are not working with clustered (grouped) or time series data correct?


Active Member
The predictor variables could be highly correlated (multicollinearity). The effects of one predictor variable are masked when other predictors are already in the model.