I am running a stepwise binary logit regression in Stata using 14 independent variables. Two of the independent variables are dummies (assuming a value of 0 or 1). I've tested the independent variables for multicollinearity and adapted them by standardizing or using the natural logarithm of their values in order to mitigate this issue (VIF<2.5). The normal model runs smoothly; however, when I want to bootstrap the sample (# of observations: 73) with 1000 replications I receive p-values of 1.0000. Furthermore, the results conclude with the note: "one or more parameters could not be estimated in 314 bootstrap replicates; standard-error estimates include only complete replications."
Two questions: 1. Is the VIF threshold that I used correct (VIF<2.5)? Which other ways are there to get rid of multicollinearity, without dropping one of the variables? 2. Since I don't assume that multicollinearity is an issue anymore, what else could I have done wrong concerning my bootstraping methodology?
Many thanks in advance for your answer(s)!