I am running a model (logistic regression) with 20 independent variables in R.
Before running the model I calculated the correlation between all the variables and finally selected my variables by also checking "visually" the histograms of each variable in the case of presence and again in the case of absence. In situations where I don't see any obvious distribution associated to both presence & absence, I discard the variable.
I would like to make "official" calculations for the level of relation between Presence/Absence and each variable (how much each variable contributes to the Presence/Absence), for example with
Cramer's V index, but the available function I find is from the package
vcd and has some limitations:
doesn't give the
Cramer's V (as well as the Phi-Coefficient Contingency Coeff.) for each independent variable, and it doesn't run for one independent variable.
I might be missing some other obvious way to do this. Any help is appreciated.