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From |
Maarten Buis <maartenlbuis@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Frailty gamma or inv gaussian distribution |

Date |
Wed, 12 Sep 2012 09:35:47 +0200 |

On Tue, Sep 11, 2012 at 9:25 PM, Alexander James wrote: > I am trying to run a survival model. I am facing an issue regarding how I should set the frailty. When I use gamma distribution I get very significant, but when I try to run it with inverter Gaussian distribution the level of significance of my main explanatory variable reduces substantially. I could not find any test to indicate which of them is more appropriate or a reference to explain why I am observing the chance in significance level. Would someone have a suggestion for this question? <snip> > ps. I am using an exponential model Conceptually, a model with gamma frailty or inverse Gaussian frailty are very similar. So if they give very different results, than the conclusion is that your models aren't robust enough to draw meaningful conclusions. So rather than trying to select one of these models a the "best", you should try to make your model more robust(*). In this case, I suspect your problem is the form of the baseline hazard that you have chosen by specifying an exponential model. Within an exponential model, you assume that the baseline hazard is constant over time. With frailty the baseline hazard will decline: the frail are selected out early, so at later points in time the more hardy remain. For more on that see: (Vaupel and Yashin 1985). If your model is wrong and the baseline hazard net of frailty is not constant over time, your model will try to assign all those changes in the baseline hazard to the frailty component, which can easily lead to an unstable model like the one you have. The solution is to try different baseline hazard functions, so try different distributions in the -distribution()- option of -streg- or try -stcox-. Hope this helps, Maarten (*) Despite the name, you are not going to achieve that by adding the -robust- or -vce(robust)- options: These refer to a completely different type of robustness. James W. Vaupel and Anatoli I. Yashin (1985) Heterogeneity's Ruses: Some Surprising Effects of Selection on Population Dynamics. The American Statistician, 39(3): 176--185 . --------------------------------- Maarten L. Buis WZB Reichpietschufer 50 10785 Berlin 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: Frailty gamma or inv gaussian distribution***From:*Alexander James <alexandre_lille-paris@hotmail.com>

**References**:**st: Frailty gamma or inv gaussian distribution***From:*Alexander James <alexandre_lille-paris@hotmail.com>

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