I am aware that having too many categorical variables in the regression model might affect degree of freedom, especially when we have a small sample size, so we should avoid it.
My questions as follow:

1) What is the effect of having too many categorical variables in the regression? Does it mean we can't trust the results?
2) Does this apply to the logistic regression model as well?
3) Any way to detect this in Stata? What would be the command?


I am currently conducting a binary regression analysis with a very small sample size, 260 samples.
I have 11-14 independent variables and most of them are categorical variables.
I am concerned my model has errors, and I want to correct it.

Could anyone give me answers to these questions?
You can answer one or two. You don't have to answer to all. It will be very appreciated..!