Posted by
Justin Blehar on
Sep 30, 2012; 12:32am
URL: http://spssx-discussion.165.s1.nabble.com/Controlling-for-Race-with-SPSS-20-tp5715386p5715388.html
The population is outpatient individuals suffering from schizophrenia. Most of the research I found either does not list race or only has Caucasians in their sample. I have a large enough N to run only Caucasians but this limits how well the results can be generalized. I'm trying to avoid this if possible.
Total Sample
Caucasian - N = 76
African American- N = 44
Groups
Never Smokers: Caucasian N = 15 African American N = 23
Former Smokers: Caucasian N = 29 African American N = 2
Nonsmokers: Caucasian N = 44 African American N = 25
Heavy Smokers: Caucasian N = 9 African American N = 5
Light Smokers: Caucasian N = 23 African American N =14
Current Smokers: Caucasian N = 32 African American N = 19
Thanks for your reply :)
V/R
Justin
________________________________________
From: SPSSX(r) Discussion [
[hidden email]] on behalf of Michael Palij [
[hidden email]]
Sent: Saturday, September 29, 2012 8:11 PM
To:
[hidden email]
Subject: Re: Controlling for Race with SPSS 20
If you control for race in whatever manner, to what population
would your conclusions apply to? And by population I mean
humans, not a mathematical distribution.
-Mike Palij
New York University
[hidden email]
On Sat, Sep 29, 2012 at 6:18 PM, Justin Blehar <
[hidden email]> wrote:
> Hello All,
>
> Not sure how much detail is needed so I'll give you a quick overall but I'm
> trying to control for race and am unsure how to best go about this. I know
> that I can run a partial correlation and control for race using the menu but
> is this really controlling for race? If not is there a better way? How would
> I do this for a t-test?
>
> This is a cross sectional design looking at cognition and smoking in a
> psychiatric population. There are six groups I'm looking at; Never Smokers,
> Former Smokers, Nonsmokers (includes both never smokers and former smokers),
> Heavy Smokers, Light Smokers, and Smokers (includes heavy and light
> smokers). I have 36 scale variables that I want to compare between each of
> these groups. When I break out the groups by race (just looking at box plots
> and mean comparisons) there are clearly some large race effects (e.g.
> parental education, level of functioning, IQ, etc...). I'd like to be able
> to correct for this in each analysis. I'm running both correlations and
> t-tests (maybe this isn't the best process?).
>
> If I run a partial correlation and control for race is this really
> controlling for race?
>
> When running the t-tests how do I control for race?
>
> Any help would be greatly appreciated.
>
> V/R
>
> Justin
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