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 <[email protected]>:
> At 09:18 AM 11/5/2003 +0000, [email protected] 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
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