I have data with about 700 observations total. There are 9 subgroups in my sample with sizes ranging from 54-96.
I want to use linear regression to explore how 8 independent variables might predict my outcome of interest, and expect patterns may be different for each of my subgroups. I don't have enough power to run a regression for any of my subgroups (I was reading that rule of thumb for regression sample size was at least N>104+k). But what if I kept my whole sample together instead of stratifying, and then did 8 different models with interactions with subgroup*each predictor? Would interaction help me explore the same general question that isn't possible with stratification due to insufficient sample size?