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From |
Karen Robson <klrobson@essex.ac.uk> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Wed, 5 Nov 2003 12:54:16 +0000 (GMT Standard Time) |

Thanks for your replies. What I am trying to calculate is if the mean of a dummy variable is different across the categories of a separate categorical variable. So if the mean of a dummy variable (e.g. let's say 1=has university degree, 0=does not have university degree) is significantly different across a nominal variable like religious affiliation which has five possible values. If I had just two categories in the religious affiliation variable, I could just prtest university, by(religion). Since I have multiple categories, however, this becomes impossible. If my DV was continuous, I could do an anova and with post-hoc estimations figure out where the significant differences between categories were. However, because my DV is not continuous, I have been told an anova here is not appropriate, hence my confusion. Perhaps I am just being pedantic? I would really appreciate your opinion now that I have fully explained myself! On Wed, 05 Nov 2003 07:17:59 -0500 Richard Williams <Richard.A.Williams.5@nd.edu> wrote: > 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 > HOME: (574)289-5227 > EMAIL: Richard.A.Williams.5@ND.Edu > WWW (personal): http://www.nd.edu/~rwilliam > WWW (department): http://www.nd.edu/~soc > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ ---------------------- Karen Robson (klrobson@essex.ac.uk) Institute for Social and Economic Research (ISER) University of Essex, Colchester, UK CO4 3SQ tel: +44 (0)1206 873897; fax: +44 (0)1206 873151 * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: k-sample tests for differences in proportions***From:*May Boggess <mboggess@stata.com>

**Re: st: k-sample tests for differences in proportions***From:*Richard Williams <Richard.A.Williams.5@nd.edu>

**RE: st: k-sample tests for differences in proportions***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**References**:**Re: st: k-sample tests for differences in proportions***From:*Richard Williams <Richard.A.Williams.5@nd.edu>

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