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I need some help understanding what values I need to put into a two-tailed logistic regression power analysis are in G*Power. I am trying to see if hypertension (my binary independent) makes a difference on having a headache (my binary dependent).

The prevalence of having a headache, irrespective of hypertension is 0.004 (from [0-1]). 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 a patient having a headache with hypertension if 0.332. I assume this is my alternative hypothesis P(headache=1|hypertension=1).

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)?

Further edit: I have a medical population. 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. 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.

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  • $\begingroup$ This is not enough information. You have no idea what the prevalence of hypertension is. You must input this value into Gpower. If you assume it is 50/50 you will not have the correct power. $\endgroup$ – AdamO Jan 31 '18 at 18:04
  • $\begingroup$ I know what the prevalence of hypertension is. But that is precisely my point, what information is required and what precise fields (within the GUI) do they go into? I will add further information to the post but I am not sure if it will help. $\endgroup$ – Anthony Nash Jan 31 '18 at 18:11

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