First query, so apologize in advance for any stupidity or "unawareness". I have a large sample, at roughly 88000 obs. But, my events for this sample (the 1's) are about .00072% of the sample.
Pretty sure that my sample suffers from rare event bias. Therefore, I am using the logistf function to run a logistic model. But not sure that this is the best method. I've read the standard King and Zeng paper. But I am just getting some unusual results. Meaning, that variables that I thought would be significant, are just not coming out that way. In addition, the df for the lrtest and extractAIC are really small, between 5 to 7 for any model that I have run.
Sorry, I can't provide screen shots or results. Work data, so not sure that I can share.