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From |
Nick Cox <[email protected]> |

To |
"'[email protected]'" <[email protected]> |

Subject |
RE: st: getting realitve risk from proportional odds ratio |

Date |
Wed, 8 Dec 2010 17:41:15 +0000 |

-mlogit- as such knows nothing of any ordering. However, if your response is genuinely ordinal, then presumably the results will echo this and you can draw upon what you know in interpretation. As very recently aired on this list, -constraint- is for linear constraints, and inequalities do not qualify as linear. (For example, a = b defines a line, but a > b defines a half-plane.) Nick [email protected] Bontempo, Daniel E Thanks Maarten - I thought the there would be this kind of problem. I am intrigued by the mlogit suggestion. Would I lose the ordered nature of my dv? The levels are not nominal, but increasing. Could I use the constraint option to specify the order? Maarten buis --- On Tue, 7/12/10, Bontempo, Daniel E wrote: > I have used "ologit dv iv, or" where my dv is 0 to 5 > reported limitations on activities of daily living. (With > such a restricted range of counts, a Poisson model did not > seem right.) I requested the odds ratio output format. > However there seems to be a lot of advice on reporting > relative risk (RR) instead of OR. I find many formulas that > calculate RR from OR and rate information for the reference > group (i.e., iv=0). But here I am unsure if what works for > OR can work for proportional OR. Since the OR is for a one > level increase in the DV, what rate can I use in the formula. I very much doubt whether the odds ratios in an ordered logit can be meaningfully transformed to risk ratios. The idea behind the ordered logit is that there are effects on the odds of getting 0 versus more, 0 or 1 versus more, 0, 1, 2 versus more, etc, and that all these effects are constrained to be equal. That is why it can give you one effect (odds ratio) for each variable. The formulas for transforming OR to RR are approximate, and I don't think they play well with the constraint implicit in the ordered logit model. My guess would be that you would get 5 (number of categories -1) different RR for each variable, so that would defeat the very purpose of the proportional odds assumption. So either I would use -ologit- and interpret results in terms of odds ratios, or I would use -mlogit- and interpret results in terms of risk ratios. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: ST: getting realitve risk from proportional odds ratio***From:*"Bontempo, Daniel E" <[email protected]>

**Re: st: ST: getting realitve risk from proportional odds ratio***From:*Maarten buis <[email protected]>

**RE: st: getting realitve risk from proportional odds ratio***From:*"Bontempo, Daniel E" <[email protected]>

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