between-subject variation in power analysis

[Norman B. Grover]

Many years ago, I read that when estimating standard deviations in power
analysis of the two-sample t-test, one should take a larger value for the
treatment group than the control group (which can usually be found in the
literature) because in biological experiments intervention often disturbs
the steady state or, for observational data, the sick group can be expected
to be less homogeneous.
I can no longer locate that reference and wonder whether anyone here can
help me by directing me either to an appropriate source for such a claim or
to actual published data.
Any help would be greatly appreciated.

[Rich Ulrich]

On Sat, 9 Jul 2016 13:51:45 +0300, Norman B. Grover

Post by Norman B. Grover
Many years ago, I read that when estimating standard deviations in power
analysis of the two-sample t-test, one should take a larger value for the
treatment group than the control group (which can usually be found in the
literature) because in biological experiments intervention often disturbs
the steady state or, for observational data, the sick group can be expected
to be less homogeneous.
I can no longer locate that reference and wonder whether anyone here can
help me by directing me either to an appropriate source for such a claim or
to actual published data.
Any help would be greatly appreciated.

Well, Jacob Cohen wrote the book on power analysis for the
social sciences. That would be the first place that I would look.

Cohen does mention practical considerations, so that might be
one of them. The consequence of knowing that variances are
unequal is that you have reason to depart from the usual practice
of sampling equal Ns in the two groups.

[Norman B. Grover]

Post by Rich Ulrich
On Sat, 9 Jul 2016 13:51:45 +0300, Norman B. Grover

Post by Norman B. Grover
Many years ago, I read that when estimating standard deviations in power
analysis of the two-sample t-test, one should take a larger value for the
treatment group than the control group (which can usually be found in the
literature) because in biological experiments intervention often disturbs
the steady state or, for observational data, the sick group can be expected
to be less homogeneous.
I can no longer locate that reference and wonder whether anyone here can
help me by directing me either to an appropriate source for such a claim or
to actual published data.
Any help would be greatly appreciated.

Well, Jacob Cohen wrote the book on power analysis for the
social sciences. That would be the first place that I would look.
Cohen does mention practical considerations, so that might be
one of them. The consequence of knowing that variances are
unequal is that you have reason to depart from the usual practice
of sampling equal Ns in the two groups.

I just replied directly to the poster, sorry. I meant to write here.

Cohen was the first place I went to, and the second. But he does not
consider the case common in experimental biology in which treatment implies
intervention (nor when a healthy control group is compared with a sample of
sick subjects) and there, I believe, the issue arises.

Yes, with unequal variances one should use unequal Ns.

Thank you Rich for your help. Sorry about the direct reply.