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From |
Maarten buis <[email protected]> |

To |
[email protected] |

Subject |
Re: st: RE: convergence problem |

Date |
Fri, 8 Jan 2010 05:31:15 -0800 (PST) |

--- On Fri, 8/1/10, Rosenstock, Summer E. wrote: > It looks like my estimates are coming in near the boundaries, > which has shown to be a problem with log-binomial regression > with continuous independent variables. THere are a couple of > articles that document this. So, looks like I'll stick to OR > on that particular variable with a foot note about > convergence. There are alternatives. Such non-convergence in these models is often a sign that the effect of your continuous variable is not linear in the log(risk). One solution is to allow that variable to have a non-linear effect. I like (linear) splines for that, as you can still easily interpret the coefficients. So in the example below for the model that converges: the basline risk of union membership for someone from the north with 0 wage is .04, this risk decreases by 35% (=100*(1-.65) if someone comes from the south, the risk increases 43% for every dollar increase in wage if the wage is less 5 $/hour, increases by 11% for every dollar increas in wage if the wage is between 5 and 10$/hour, and decreases by 3% for every dollar increase in wage if the wage is more than 10$/hour. *--------- begin example ------------ sysuse nlsw88, clear gen baseline = 1 *does not converge glm union south wage baseline, /// link(log) family(binomial) /// iter(50) eform nocons *converges mkspline w1 5 w2 10 w3 =wage glm union south w? baseline, /// link(log) family(binomial) /// eform nocons *----------- end example ------------ ( For more on how to use examples I sent to statalist see: http://www.maartenbuis.nl/stata/exampleFAQ.html ) Hope this helps, Maarten Ps. I know it is an old complaint of mine, but I haven't made it in a while, so I'll indulge in it again: I think that the -eform-, -or-, -irr-, -rrr-, etc. options should not suppress the display of the constant. These are important in judging the size of the effect. Knowing that the odds, risk, incidence rate, or relative risk doubles for a unit change in x can be meaningfully supplemented by information about the baseline value: twice a very small number is still a very small number but twice a large number is a huge number. -------------------------- 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/

**References**:**st: RE: convergence problem***From:*"Rosenstock, Summer E." <[email protected]>

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