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From | "Clyde Schechter" <clyde.schechter@einstein.yu.edu> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: Re: st: Subgroup analysis |
Date | Thu, 8 Jul 2010 06:33:01 -0700 |
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: clyde.schechter@einstein.yu.edu * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/