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Re: st: Subgroup analysis
From
David Bai <[email protected]>
To
[email protected]
Subject
Re: st: Subgroup analysis
Date
Thu, 08 Jul 2010 10:23:44 -0400
Thank you, Clnde. I have looked at the coefficients in the white and
African American subgroups, and found that they are not very close. So
there is no evidence of a lack of statistical power, based on what
you've suggested. Regarding the second suggestion, I have good reasons
to believe that some interactions could be significant based on the
subgroup analysis.
Maybe I didn't make it clear in my last inquiry, so let me clarify
here: My concern is not about whether the interaction effect is
significant, but how to interpret the UNEXPECTED differential
predictors' effects on the outcome across race/ethnicity if the
interaction effect is significant. Assuming my analysis is correct, and
found differential effects across race/ethnicity, but there is NO good
theory to explain this difference, how can we explain it from
statistical perspective? Lack of statistical power, with 28 predictors
for a sample size of 600? Or African Americans are very homogeneous in
the distributions of these predictors, and therefore it is hard for the
analysis to distinguish any variations in the effects and therefore
find non-significance in the results? or other interpretations?
Looking forward to more wisdom/insight to be shared with me. Thank you,
David
-----Original Message-----
From: Clyde Schechter <[email protected]>
To: [email protected]
Sent: Thu, Jul 8, 2010 9:33 am
Subject: Re: Re: st: Subgroup analysis
Comparing the statistical significance of effects in two sub-populations
is rather perilous.
I have two suggestions. First, since you have already done the
race-specific analyses, just look at the coefficients in the White and
African American subgroups, disregarding standard errors and p-values.
Are the coefficients similar? If so, you may well be simply finding a
lack of statistical power to detect in a subgroup of 600 subtle effects
that achieve statistical significance in your larger combined sample.
Second, and more formally, before even running the subgroup analyses, I
would have added race X predictor interaction terms to the model and
then
tested the significance of those interaction terms. If _they_ are not
significant, then the conclusion would be that your data do not provide
evidence of difference across races (which is not the same as evidence
of
no difference across races). If the interaction terms _are_
significant,
then the coefficients of those interaction terms give you estimates of
the
cross-race differences in effects.
Hope this helps.
Clyde Schechter, MA MD
Associate Professor of Family & Social Medicine
Please note new e-mail address: [email protected]
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