I often hear from statistical experts (including on this site) that simulation is the preferred method to calculate power for a clinical trial (rather than using traditional sample size calculation formulae).
I use Stata, and I was wondering if anyone can show me how to do this in detail?
For example, two scenarios:
1) Continuous variable: A new drug given intraoperatively is hypothesized to result in a reduction in the mean troponin release from 2.2 to 1.8 (SD of both 2.0) after cardiac surgery, compared to placebo.
2) Proportions: A sexual educational intervention is hypothesized to result in a reduction in the incidence of HIV transmission amongst teenagers from 20% to 15%.
Assuming a power of 80% and an alpha of 5%, in Stata, I would normally type the following:
sampsi 2.2 1.8, sd(2) power(0.8) Estimated sample size for two-sample comparison of means Test Ho: m1 = m2, where m1 is the mean in population 1 and m2 is the mean in population 2 Assumptions: alpha = 0.0500 (two-sided) power = 0.8000 m1 = 2.2 m2 = 1.8 sd1 = 2 sd2 = 2 n2/n1 = 1.00 Estimated required sample sizes: n1 = 393 n2 = 393
and for 2) I would type:
sampsi 0.2 0.15, power(0.8) Estimated sample size for two-sample comparison of proportions Test Ho: p1 = p2, where p1 is the proportion in population 1 and p2 is the proportion in population 2 Assumptions: alpha = 0.0500 (two-sided) power = 0.8000 p1 = 0.2000 p2 = 0.1500 n2/n1 = 1.00 Estimated required sample sizes: n1 = 945 n2 = 945
Can anyone please show me how the simulation technique might look in Stata for these two examples?