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| From | "Garth Rauscher" <garthr@uic.edu> |
| To | <statalist@hsphsun2.harvard.edu> |
| Subject | RE: st: Odds ratio |
| Date | Sat, 10 Apr 2010 17:05:42 -0500 |
In my discipline (epidemiology) we have relied heavily on odds ratios simply out of habit and convenience (logistic regression) when our interest is almost never in the OR itself, but rather in the risk or prevalence ratio or difference. Because of past help I have received on this list I have learned how to convert model-based predictions from logistic regression into risk ratios or differences using marginal standardization with bootstrapped confidence intervals. The syntax is fairly straghtforward. I don't know what the implication would be if predictions were generated from a random intercept or gee logistic model. Does anyone have additional thoughts about this that might help to answer Rosie's original problem? Garth Rauscher UIC School of Public Health -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Lachenbruch, Peter Sent: Friday, April 09, 2010 11:24 AM To: 'statalist@hsphsun2.harvard.edu' Subject: RE: st: Odds ratio I almost agree - ORs are tough to interpret for non-Epidemiologists and Statisticians. However, logistic regression is designed to estimate log-odds ratios. I'd report both so both of you can feel 'happy' - of course, if the difference in probability of event is tiny, a large OR doesn't really indicate a big issue Tony Peter A. Lachenbruch Department of Public Health Oregon State University Corvallis, OR 97330 Phone: 541-737-3832 FAX: 541-737-4001 -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of E. Paul Wileyto Sent: Thursday, April 08, 2010 12:17 PM To: statalist@hsphsun2.harvard.edu Subject: Re: st: Odds ratio The problem is that vastly different sets of numbers can give you the same odds ratio... same odds ratio, with different variances. Effect size (in Cohenesque d speak) is best obtained from fractions and and changes in fractions. Your effect size can come from the log of the odds-ratio, but the variance will be determined by the actual proportions involved in calculating the OR. It doesn't sound like the reviewer is asking for much. Would it hurt to give the proportions? You can actually generate those effect size numbers (d) if you report an Odds Ratio with CI95 and a sample size, but that is more convoluted. P Rosie Chen wrote: > Hello, dear all, > > I have a question regarding a reviewer's comment on my use of odds ratio in interpreting the results of a logistic regression, and would appreciate it very much if you can provide any insight or any references for responding to the comment. > > The reviewer commented that all results are expressed in terms of odds ratios which makes it very difficult to assess the magnitude of the effect. Probabilities and changes in probabilities would be much easier to interpret. My impression is that, although it is true that predicted probabilities might be easier to understand, odds ratios have been used extensively in research when we interpret results from logit models. > Do you have any suggestions regarding how to respond to this comment, or do you have any statistics textbooks in your mind that recommend odds ratio as a standard approach reporting results from logistic models? > > Thank you very much in advance! > > Rosie > > > > > * > * 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/ > > -- E. Paul Wileyto, Ph.D. Assistant Professor of Biostatistics Tobacco Use Research Center School of Medicine, U. of Pennsylvania 3535 Market Street, Suite 4100 Philadelphia, PA 19104-3309 215-746-7147 Fax: 215-746-7140 epw@mail.med.upenn.edu * * 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/ * * 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/ * * 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/