This is a repost from stackflow forum. My purpose is to discover key relationship between variables. I have several categorical variables such as "nationality, office locations, job title" etc. In total I have 14 categorical which created about 100 dummy variables and 6 continuous variables.
My dependent variable is binary outcome, hence, logistic regression is used ( input all variables at one go). I encountered multiple warning messages that these variables are omitted due to collinearity in the result. In this scenario, are there any methods to "treat" these dummy variables to be able to include them in the model? Or I should use other methods of regression or other techniques to resolve?
Below is a sample of the result: