Help about sample size calculationFor my study, the primary endpoint is to determine the proportion of patients who experience a beneficial effect after receiving the treatment. We have established a null hypothesis proportion (𝐻0) of 0.5, indicating our expectation that approximately 50% of the patients will exhibit a beneficial response to the treatment post-intervention. This figure serves as a clinically relevant cut-off point for effectiveness in our analysis.
Furthermore, previous research has shown a proportional effect of 0.74 for similar treatments. We have consequently chosen this figure as our alternative hypothesis (𝐻𝑎), proposing that the new drug will demonstrate an effect size at least as large as this benchmark.
Given these parameters, we have conducted preliminary sample size calculations to ensure adequate power for our study. Nonetheless, we seek validation of our methodology and assistance to confirm that our approach aligns with best practices and that our sample size is sufficient to detect a significant difference between the null and alternative hypotheses.
I typed it to JMP (in the picture) as 0.5 and 0.74 and have a result of 35
I want to ask the community if I am doing the right thing about the sample size calculation?
Advanced Statistical ModelingRe: Help about sample size calculationHi @thiennguyen : You want to show your treatment’s proportional effect is 0.74 or more. Correct?
So, Ha is p>=0.74. Ha is always what you want to show. Then, HO is the opposite of Ha. HO is p<0.74. So this is a one sided test. Your assumed proportion must be somewhere in Ha. After all, if you don’t think Ha is true, then why do the study? Furthermore, if your assumed p is in H0 you will have power <= 0.05 (and if you assume p=0.74, then power = alpha = 0.05). So, to answer your question, no you don’t have it right 
