Multivariable Logistic in R, without the "reference" level in a categorical predictor I am dealing with the following problem: 
I have to do a multivariable logistic in R, using the command glm with the  argument family = binomial.
The dependent variable is (obv) a binary variable (worker) with a Yes/No outcome and the predictors are gender, student and type of event. gender and student are binary variables, while type of event is categorical with 5 possible outcomes.
When applying the logistic, in the outcome are shown only 4 levels of the variable type of event, using the other remaining level of that variable as a "reference" one. What I would like to have in the outcome is to maintain 1 level for the two binary variables (in my case genderMALE and studentYES), and to have the 5 levels for the categorical variable type of event, but I don't know how to do it.
I was wondering if there were any arguments of this function that could solve this.
I thought of using something as model.matrix but I am not sure this is the best solution.

This is better solved at the summary stage. There is really a hidden coefficient for the omitted level, but as it is fixed by zero, the usual summaries ignores it. There is a special R package that does include those, gtsummary.
For details and examples see What to do in a multinomial logistic regression when all levels of DV are of interest?
