Sample size for a paired t-test

#1
Hello all

I have a simple question. I need to calculate a sample size for a study that will be analyzed with a paired t-test.

One of the input parameters for the calculation, is the standard deviation of the differences. However, I do not know it. What I do know, is the standard deviation of the first group and the standard deviation of the second group.

Each subject will receive two treatments. A continuous measure will be taken after each. I know what is the standard deviation of the measure after the 1st treatment and I know what is the standard deviation of the measure after the 2nd treatment, but the standard deviation of D, I don't know.

SAS proc power allows to enter the standard deviations I do know, but I have no idea how from there they estimate the difference standard deviation. PASS on the other hand (which is a remarkable sample size software) asks directly for the difference standard deviation, which I don't know.

My question is, how do I estimate the difference standard deviation ? Via simulation ?
 
#3
this is probably somehow correct, however I have one slight problem. In order to calculate a pooled variance I need N, which is my unknown parameter in the first place.
 
#6
I found it:

\(\sigma _{diff}=\sqrt{\sigma _{1}^{2}+\sigma _{2}^{2}-2\cdot \rho \cdot \sigma _{1}\cdot \sigma _{2}}
\)

(sorry about LateX, don't know what's wrong)

I saw it in SAS details manual, however, I still don't know where this formula came from (anyone recognize it ?)

I tried the formula and I have some answers. PASS calculates using a 0 correlation, I tried calculating the standard deviation of differences using the formula with correlation 0, ran it in Gpower you recommended, and got a match.

Then I used correlation 0.3 and 0.5, but in Gpower and SAS, and got a match.

What I am saying is, that all software are working fine, I only wish I knew this formula, could have saved me a long long time.

The nice part, I tried simulating data with means and standard deviations like mine, and got same result like the formula gave...
 
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