My situation:
- small sample size: 116
- binary outcome variable
- long list of explanatory variables: 50
- explanatory variables did not come from the top of my head; their choice was based on the literature.
Following a suggestion to a previous question of mine, I have run LASSO (using R's glmnet package) in order to select the subset of exaplanatory variables that best explain variations in my binary outcome variable.
I have calculated lambda.min through cross-validation (cv.glmnet command) and got the correspondent coefficients for my explanatory variables. For 6 of my total 50 explanatory variables, the coefficients were non-zero. Are those coefficients comparable, i.e. can I say that the variables with the highest ones are the most important? If they are not comparable, can I run logistic regression (using glm) with those 6 variables and then compare them in terms of coefficients and p-values?
