Non significant regression

Hi all,

I have what is surely an embarrassingly basic question.

I am looking at the relationship between a specific medical diagnosis and unplanned admission to the hospital following outpatient surgery. My dataset has 100 patients. 77 without the diagnosis, 23 with. 5 patients in the dataset were admitted following surgery. All of them have the medical diagnosis.

Thus, it would seem that the diagnosis increases the odds of admission. However, when I perform the logistical regression analysis, it’s not significant with a p value of nearly 1. Why is this?

Thank you!!


Less is more. Stay pure. Stay poor.
Not near a computer, so i cant run these numbers. Given the rarity of the outcome perhaps you cannot rule out chance given the small dataset.Though I am surprised the model converged. Can you post the model's output to confirm it ran correctly.

Typically when you have a small sample and complete separation you need to use the Firth penalization.
Thanks for your response! Here is my SPSS output. Your idea that it's due to the small sample size and chance is what I was thinking, considering the Classification tables for both the block 0 and block 1 are the same, even with the inclusion of the medical condition (OSA).

Any idea how to run the Firth penalization in SPSS?

Many thanks

Block 1.PNG
Block 2.PNG
Block 3.PNG