I know how to run multiple regressions (SMR, HMR, and MMR) in SPSS but I'm still a little vague on when it's appropriate to use each of them to achieve the best and most parsimonious result. (SPSS being the mathematical software, SMR being standard multiple regression, HMR being hierarchical multiple regression, and MMR being moderated multiple regression, SMR and SPSS are further explained in this video, hierarchical multiple regression in this video, and moderated multiple regression in this blog post).
e.g. in a case where I want to see the impact of social anxiety, and sense of humour on life satisfaction, I hypothesise that both social anxiety and sense of humour will be individually associated with life satisfaction.
When controlling for age, gender and anxiety, participants high in sense of humour will have higher life satisfaction.
Also, when excluding variables of age and gender, I predict that the negative association between anxiety and life satisfaction will be stronger for those with low sense of humour ratings.
I feel that for most of these questions, the answers could be found using an SMR, and the last question, with an MMR, but is there a simpler and more parsimonious way to do this? Can I gather the data for the first few questions from the MMR analysis, for example?