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Re: st: Subgroup analysis


From   David Bell <dcbell@iupui.edu>
To   <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Subgroup analysis
Date   Wed, 7 Jul 2010 16:13:35 -0400

David-

How about collinearity issues in your African American subsample?  Twenty-eight predictors would make me nervous.  

Dave
====================================
David C. Bell
Professor of Sociology
Indiana University Purdue University Indianapolis (IUPUI)
(317) 278-1336
====================================




On Jul 7, 2010, at 3:35 PM, David Bai wrote:

> Thank you, Dave. The African American group has 600 cases, and there are 28 predictors in the model. The same 28 predictors are used for all subgroup analysis.
> 
> David B
> 
> 
> -----Original Message-----
> From: David Bell <dcbell@iupui.edu>
> To: statalist@hsphsun2.harvard.edu
> Sent: Wed, Jul 7, 2010 3:18 pm
> Subject: Re: st: Subgroup analysis
> 
> 
> So how large is your African American subsample?  Maybe your power is much lower
> in that subsample.  Or maybe your model is well specified for Whites but not for
> African Americans.
> 
> Dave
> ====================================
> David C. Bell
> Professor of Sociology
> Indiana University Purdue University Indianapolis (IUPUI)
> (317) 278-1336
> ====================================
> 
> 
> 
> 
> On Jul 7, 2010, at 2:35 PM, David Bai wrote:
> 
>> Hi, all,
>>    I would like to compare predictors' effects across different 
> racial/ethnic
> groups, so I first ran a comprehensive model including all groups, and then used
> subpop function in stata to do subpopulation analyses for each ethnic group.
>>   What the results show is that many (not just a few) significant 
> predictors
> in the comprehensive model (including all racial groups) become non-significant
> in the African American group, while the White group's results are similar to
> the results of the comprehensive model. How can I interpret all these? Is it
> possibly because 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
> is it because the sample size of this group is relatively small compared with
> other groups (e.g., whites)  in the sample? Are there any other possible
> interpretations? Your insight will be appreciated.
>> 
>>     David B
>> 


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