I know that sample size affects power in any statistical method. There are rules are thumb for how many samples a regression needs for each predictor.
I also hear often that the number of samples in each category in the dependent variable of a logistic regression is important. Why is this?
What are the actual consequences to the logistic regression model when the number of samples in one of the categories is small (rare events)?
Are there rules of thumb that incorporate both the number of predictors and the number of samples in each level of the dependent variable?