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

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Odds ratio |

Date |
Fri, 9 Apr 2010 07:14:40 +0000 (GMT) |

--- On Fri, 9/4/10, Rosie Chen wrote: > I am doing HLM analysis, so it is impossible to use the Stata > syntaxt to calculate the predicted probability. So I will > just do the calculation by myself in excel. Here is what I > plan to do: I will calculate log-odds and then convert > them into predicted probabilities for individuals with > characteristics that I am interested in so as to demonstrate > the magnitude of the effect for a specific variable. Sorry for being blunt but that is a very bad idea. There are very good reasons why Stata isn't giving you those probabilities directly: These multilevel models take into account group level variation, while your approach doesn't. > For example, in order to explain the gender difference in the > probability of an outcome, I will compute the difference in > the predicted probability between females and males I am not so negative about odds ratios as others are: Odds ratios and risk differences answer subtly different questions. An effect is a comparison of groups, in your case men and women. That comparison can be made in absolute terms (i.e. compute a difference) or in relative terms (i.e. compute a ratio). Both have their advantages and disadvantages. A discussion of that is given in this paper (if I am allowed some shameless self-promotion): <http://www.maartenbuis.nl/wp/interactions.html>. The key issue with odds ratios is that I would like to have the baseline odds present, to help me interpret the odds ratio (which in a sense helps to bridge the gap between absolute and relative effects). The problem is that by default Stata suppresses those. The trick is to add a variable baseline, which is always one, and add the -noconstant- option. This trick is discussed in the paper I refered to before, and I learned it from: Roger Newson (2003), Stata tip 1: The eform() option of regress. The Stata Journal, 3(4): 445. <http://www.stata-journal.com/article.html?article=st0054> I am slowely getting used to odds, so the distinction between odds and probabilities doesn't bother me any more: You can quantify the likelihood of an event by computing the expected number of success per 100 trials (100*probability) or by the expected number of success per failure (the odds). Just don't mix the two up, as sometimes happens when people try to interpret odds ratios as risk ratios. Hope this helps, Maarten -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * 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/

**Follow-Ups**:**Re: st: Odds ratio***From:*Richard Williams <Richard.A.Williams.5@ND.edu>

**RE: st: Odds ratio***From:*"Mak, Timothy" <timothy.mak07@imperial.ac.uk>

**References**:**Re: st: Odds ratio***From:*Rosie Chen <jiarongchen2002@yahoo.com>

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