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I already know from the literature that your odds go up! And my piolet study shows that hypertension is the most prevalent of comorbidities in the headache cohort.Armitage, P., Berry, G., & Matthews, J.

I am only interested in records with a headache diagnosis, but I want to determine what set size I require measuring an increase or decrease in odds given the presence (exposure) to hypertension. Is this what I need to add into the probability textboxes, and what do I add into the X param pi (I think this is the proportion of some distribution)? I assume this is my alternative hypothesis P(headache=1|hypertension=1). The prevalence of a patient having a headache with hypertension if 0.332. I assume this is my null hypothesis P(headache=1|hypertension=1) i.e., hypertension does not impact the outcome of a headache. The prevalence of having a headache, irrespective of hypertension is 0.004 (from ). I am trying to see if hypertension (my binary independent) makes a difference on having a headache (my binary dependent). I need some help understanding what values I need to put into a two-tailed logistic regression power analysis are in G*Power.

Logistic regression gpower