I've been performing some logistic regressions and found some great results. The problem is I'm unsure if my model is stable or not. This is mostly because I am confused about what people mean by cell size for logistic regression.
I keep reading inconsistent prescriptions. Some people say I need 10-15 observations per variable while some people say I need 10-15 observations per cell. I also get confused if people mean per cell when including all variables or just the main exposure/control vs event/ no event.
The overall N is 331.
Let's say I have data in a 2x2 table with the typical exposure/control by event/ no event:
. Event No Event . . Exposure 103 15 . . No Exposure 150 63
In this example, the smallest cell size would be 15. So, I could perform a logistic regression with 1 independent variable, right?
So let's say I wanted to add another variable to the same data, like Race (African American or not, 1 or 0) and here's the cell breakdown:
. Clinic Event Race N . 0 1 1 121 . 1 1 1 92 . 0 0 1 46 . 0 1 0 29 . 0 0 0 17 . 1 0 1 14 . 1 1 0 11 . 1 0 0 1
Would this now mean that my smallest cell is 1? Or, would I still refer to the original 2x2 table and it would still be 15?
I'm asking because when I run my logistic model in SAS with 6 independent variables on this same data, I do not get any small cell warnings and the convergence criteria is met. Does this mean I'm okay and don't need to necessarily worry about cell size?
I have been running exact logistic regression models anyway but they take a VERY long time (whole other story). I'd rather just report the standard LR results to save time (assuming they are legitimate).