Justifying use of hierarchical multiple linear regression (MHLR)


My research question is looking at the predictors of the transfer of training.

I have performed a series of separate hierarchical multiple linear regression analyses (one for each of the dependent variables i.e. the learning outcomes of the training).

I entered control variables in step 1 (e.g. age, gender, pre-training baseline scores) and then in step 2 entered my main variables of interest (post-training support and the opportunity to apply the learning).

My rationale for using this statistical technique was that it allows me to effectively control for predictors, and see the additional variance explained for by my predictor variables of interest.

However, I'm now just preparing for my viva and the inevitable questions about why I think this approach is best. I've started thinking about ANCOVA and I think that this could have pretty much achieved the same thing?

Are there any benefits of using HMLR, or is it just a matter of preference?