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From |
Maarten buis <maartenbuis@yahoo.co.uk> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Incidence rate ratio |

Date |
Thu, 6 Mar 2008 15:20:01 +0000 (GMT) |

--- Mohammed El Faramawi <melfaram@yahoo.com> wrote: > I am trying to calculate the incidence rate ratio(IRR) > for a categorical variable ( Mortality) which has > two categories only ( dead or alive) in a probability > weighted sample. I am also trying to adjust for > covariates. I know that poisson regression can be used > to calculate (IRR) and adjust for covariates given > that the outcome is a count for example the number of > deaths, number stroke attacks, etc . My question is > what regression should I use in such a situation i.e > outcome which is not count.Can I still use poisson > regression which I doubt it?? Thank you --- wangxin wrote: > so, your dependent variable is dead or alive? that is > a binary one. you may use Logistic regression. -logit- will give you odds ratios instead incidence rate ratios (or risk ratios as they are often called in case of a binary dependent variable). There are people who think that odds ratios are too dificult to understand, for that reason prefer risk ratios or even risk differences. I disagree. For various views on this you can follow the thread starting with: http://www.stata.com/statalist/archive/2008-01/msg00308.html One problem with risk ratios is that it implies a model which can result in predicted probabilities larger than 1 if you have a continuous explanatory variable or multiple discrete explanatory variables. If you are willing to live with that, than you can use -poisson- to estimate this model. Alternatively, you can use -glm- with the -family(binomial) link(log)- options. The advantage of the latter command is that it warns you when your model results in predicted probabilities larger than 1. Hope this helps, Maarten ----------------------------------------- Maarten L. Buis Department of Social Research Methodology Vrije Universiteit Amsterdam Boelelaan 1081 1081 HV Amsterdam The Netherlands visiting address: Buitenveldertselaan 3 (Metropolitan), room Z434 +31 20 5986715 http://home.fsw.vu.nl/m.buis/ ----------------------------------------- __________________________________________________________ Sent from Yahoo! Mail. The World's Favourite Email http://uk.docs.yahoo.com/nowyoucan.html * * 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/

**References**:**st: Incidence rate ratio***From:*Mohammed El Faramawi <melfaram@yahoo.com>

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