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Re: st: k-sample tests for differences in proportions


From   "\"Jingky P. Lozano\"" <jlozano@apoy.upm.edu.ph>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: k-sample tests for differences in proportions
Date   Wed, 05 Nov 2003 22:37:35 +0800 (PHT)

I was thinking that you can probably use Kruskall-Wallis which is the nonpar 
equivalent of ANOVA but since you only have two possible answer (with Univ and 
without univ degree) per religion, I agree that you can just simply use chi-
square.  There will really be not much use in comparing the means.  A 0.5 mean 
in education variable cannot be interpreted as incomplete Univ degree since 
your coding system is categorical.  I think it is more appropriate to use chi-
square. 


Quoting Richard Williams <Richard.A.Williams.5@nd.edu>:

> At 09:18 AM 11/5/2003 +0000, klrobson@essex.ac.uk wrote:
> >Is there an established equivalent command to "prtest" for
> categorical
> >variables with more than two categories?
> >
> >If not, just 'how wrong' is it to use an anova estimation for this
> purpose?
> >
> >Thanks for any guidance.
> 
> I just tried the csgof command suggested by Ronan Conroy for a single 
> variable, and it works as I would expect it to.  In SPSS, you would use
> the 
> NPAR test command for this purpose.
> 
> But, are you talking about comparing proportions between 2 variables,
> e.g. 
> Var1 and Var2, each has 5 categories, and you want to test whether the
> 
> proportion in each category is the same for each variable?  If so, I
> don't 
> understand why you would consider Anova, since you'd be computing means
> of 
> a categorical variable.  If csgof doesn't give you what you want,
> perhaps 
> you could give a specific example of what it is you want to test.
> 
> Incidentally, I have "cheated" and used Anova to test p1=p2, where p1 is
> 
> the proportion of successes in the first group and p2 is the proportion
> of 
> successes in the 2nd group.  That is, both my IV and DV were 
> dichotomies.  At least in the large samples I tried it on, I got almost
> 
> exactly the same results you get by doing it the "right" way.  But, once
> 
> you get past 2 categories on your categorical dependent variable, Anova
> 
> doesn't make any sense to me.
> 
> 
> -------------------------------------------
> Richard Williams, Associate Professor
> OFFICE: (574)631-6668, (574)631-6463
> FAX:    (574)288-4373
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> EMAIL:  Richard.A.Williams.5@ND.Edu
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> 
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