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From |
Joseph Coveney <jcoveney@bigplanet.com> |

To |
Statalist <statalist@hsphsun2.harvard.edu> |

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

Date |
Thu, 06 Nov 2003 15:07:57 +0900 |

Richard Williams wrote: -------------------------------------------------------------------------------- Just as a sidelight, I took Joseph's data and ran one of the "right" commands, xi : logit degreed i.religion I got a chi-square of 1.86 with 4 d.f., significant at the .7615 level. Then, I ran a totally inappropriate horribly flawed Anova, oneway degreed religion, tabulate and got an F of 0.46 with df = 4, 295, significant at the .7623 level. Fisher's exact test came up with .775. So, anybody who happened to be using the .7616 level of significance for their decision-making would have badly screwed up here if they'd done it the wrong way. For everyone else, the difference between the right and wrong approaches is virtually non-existent. Doing the same things with the different data set generated by May's commands, the chi-square was 12.53 with 4 d.f. and the F was 3.19 with df = 4, 295. In both cases the level of significance for the test statistic was .0138. Fisher's Exact test came up with .015. Given that more than one person has probably mishandled a problem like this, it is nice to know that there is a good chance they reached the right conclusion anyway. -------------------------------------------------------------------------------- In general, if you wish to use -anova- for binary data, I recommend first transforming the dependent variable (logit transformation works well) after -collapse-, and then performing weighted -anova- using the inverse of the variance as the analytical weight. The details (formulas) can be found in the user's manual for -glogit-. Actually, -glogit- and -gprobit- produce an ANOVA table for you, so it will be much more convenient just to use either of these commands for the ANOVA, unless you prefer a different transformation. Joseph Coveney * * 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:*klrobson@essex.ac.uk

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