I use Lasso logistic regression in order to identify a smaller subset of important variables. I start with N=51 (28/23) and 32 predictors.
So far it looks pretty promising, because I can identify four important predictors in my optimal model.
Now I would like to take those four predictors and examine them along with some control variables in a standard logistic regression.
My question is, does that analysis strategy make sense? Is there a better way to include controls or other variables that might be interesting?
For a better understanding:
Identify important variables via Lasso logistic regression
Do further analysis including identified predictors and other control variables using standard logistic regression (using AIC to check model fit)