Hi,

I'm having a problem reconciling the sample size calculations with sampsi. which seem to be a bit off.

I'm using STATA 12 for Mac.

I am reviewing a research protocol where Drug A and Drug B are being used to look at chronic post-operative pain 1 year out. The expectation is that Drug A will result in pain 30% of the time, and the Drug B 10% of the time, with 80% power and a 95%confidence level.

Thus :

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However, after doing some back of the enveloppe calculations where n = 2 *(zα/2 + zβ ) ^2*p∗ (1 − p∗ ) / delta^2

and I got after some rounding n=63.

Confused by this discrepancy, I checked my math with R and got:

I cannot understand why the sample size estimate with sampsi is larger than either my hand calculations or R. I tried looking at the base code with viewsource but nothing obvious jumped out at me.

I would appreciate if anyone could point out to me where the error is. If I have done something very silly please be kind.

Thanks,

Chris Labos

I'm having a problem reconciling the sample size calculations with sampsi. which seem to be a bit off.

I'm using STATA 12 for Mac.

I am reviewing a research protocol where Drug A and Drug B are being used to look at chronic post-operative pain 1 year out. The expectation is that Drug A will result in pain 30% of the time, and the Drug B 10% of the time, with 80% power and a 95%confidence level.

Thus :

_____________________________________

Code:

. sampsi .30 0.10, power(0.8) alpha(0.05) 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 = 0.3000 p2 = 0.1000 n2/n1 = 1.00 Estimated required sample sizes: n1 = 72 n2 = 72

However, after doing some back of the enveloppe calculations where n = 2 *(zα/2 + zβ ) ^2*p∗ (1 − p∗ ) / delta^2

and I got after some rounding n=63.

Confused by this discrepancy, I checked my math with R and got:

Code:

> power.prop.test(p1=0.3, p2=0.1, power=0.8) Two-sample comparison of proportions power calculation n = 61.5988 p1 = 0.3 p2 = 0.1 sig.level = 0.05 power = 0.8 alternative = two.sided NOTE: n is number in *each* group

I would appreciate if anyone could point out to me where the error is. If I have done something very silly please be kind.

Thanks,

Chris Labos

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