I am conducting a project where I have to conduct regression on a data set with rather large amount of variables and am in need of some help.
To give some context, we are looking at whether certain prognostic variables make individuals more likely to undergo surgical or non-surgical treatment. There are a variety of variables, which are grouped into different prognostic categories (each category has 3 to 20 different variables). Categories include past medical history, which may include the presence of hypertension, obese, etc. These prognostic variables are usually binary, but can also be categorical with >2 categories or continuous.
From my understanding, I would conduct some sort of multinomial logistic regression, where the outcome is surgical or non-surgical treatment (categorical). However, I am uncertain whether I should include all variables in this model or conduct several logistic regressions for the prognostic categories. I also am wondering what other considerations I should have when conducting this analysis.
I would like to use either R or SPSS to conduct this analysis.