I don't have much experience using logistic regression and therefore I wanted to pick your thoughts for what I should do with my model.
I am using logistic regression to see how do different variables affect my dependent variable. I have 30 independent variables and some of them are dummy variables. I have used the
glmnet function to select the variables with which I can build my model and here comes my problem. As dummy variables I have for example the days of the week, however in the output from the
glmnet function I can see that some of them are in the final model and some of them are not. Would you recommend using all the dummy variables in the model or should I use only the ones that improve the performance?
Or if you could recommend articles about application of logistic regression when you want to explain the relationships between the dependent and the predictors.