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Re: st: Subgroup analysis
From
David Bai <[email protected]>
To
[email protected]
Subject
Re: st: Subgroup analysis
Date
Wed, 07 Jul 2010 18:18:56 -0400
I checked the VIF test and didn't find any collinearity issues.
Correlation test does not show high correlations either.
Would 28 predictors (mostly are dummy recoding variables of major
variables found in the literature) be too many for a sample size of
600? Would you consider that there might be sth wrong with my analysis?
IAssuming the results are correct, can I interpret this as 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 other interpretations?
Some of the predictors that are often significant for student success
(e.g., parental education, educational aspiration) are significant in
my white subsample, but not in the African American student sample,
which does not sound reasonable to me. So I am trying to figure out
whether there is sth wrong. If nothing wrong, how to interpret the
result....Thanks to Dave and anyone else who could provide any insight.
David
-----Original Message-----
From: David Bell <[email protected]>
To: [email protected]
Sent: Wed, Jul 7, 2010 4:13 pm
Subject: Re: st: Subgroup analysis
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 <[email protected]>
To: [email protected]
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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