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From |
"Stephen P. Jenkins" <stephenj@essex.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: pgmhaz/hshaz output, why does it look like this? |

Date |
Fri, 20 Feb 2009 10:00:52 -0000 |

=========================== Date: Thu, 19 Feb 2009 10:30:50 +0100 From: Hilde Karlsen <Hilde.Karlsen@hio.no> Subject: st: pgmhaz/hshaz output, why does it look like this? Dear statalisters, I am having trouble understanding why the result of my pgmhaz-command ends up like shown in the output below. (Why are there "missing" values on several of the estimates?) Does this imply I should not use pgmhaz for my discrete time hazard analysis? I've tried hshaz, but it yielded the same result. Moreover, constructing the baseline hazard in a different manner (for example log(time), or creating finer time units with dummy variables) also does not solve this problem. I am trying to find out wether there is significant heterogeneity in the data, and the first analysis (nocons) suggested statistically significant frailty. Should I rather be using a different command/program? Here is my syntax and output; I hope it is readable. . pgmhaz year1_4 year5_7 year8_10 male, i(LPNR) s(year) d(movedout) PGM hazard model with Gamma heterogeneity Number of obs = 16181 Model chi2(3) = . Prob > chi2 = . Log Likelihood = -1003.6567957 movedout Coef. Std. Err. z P>z hazard year1_4 -.5213477 .1809304 -2.88 0.004 year5_7 -.0568201 . . . year8_10 .1837397 .218296 0.84 0.400 _cons -4.199123 .1344249 -31.24 0.000 ln_varg _cons -14.54299 . . . Gamma variance, exp(ln_varg) = 4.831e-07; Std. Err. = 0; z = . - -------- Regards, Hilde =========================== If you wish to include dummy variables for all of the year* duration intervals, then you need to exclude the constant term from the regressor list. (Alternatively, drop one of the year* variables.) In short, you have a perfect collinearity issue with your syntax. The same applies to -hshaz- syntax use. I am sceptical about your claim that the same problem arose when you used log(duration) instead of the year* dummies. But then, contrary to Statalist FAQ recommendations, you haven't showed exactly what you typed in that case. An estimate of -14.5 for log(gamma variance) implies an estimate of the gamma variance of near-enough zero. This is probably telling you that frailty (unobserved heterogeneity) is hard to find with your data. You can investigate this further by tracing the path of estimates at each step, and experimenting with different starting values for the log(gamma variance). Fix the collinearity issue first though. I strongly recommend reading the appropriate Lesson at my website (and the help files) for discussion of these issues, with illustrations. URL is in my signature below. Finally, you should update and use -pgmhaz8- rather than -pgmhaz- (assuming you have version 8 or higher) Stephen ------------------------------------------------------------- Professor Stephen P. Jenkins <stephenj@essex.ac.uk> Director, Institute for Social and Economic Research University of Essex, Colchester CO4 3SQ, U.K. Tel: +44 1206 873374. Fax: +44 1206 873151. http://www.iser.essex.ac.uk Survival Analysis using Stata: http://www.iser.essex.ac.uk/iser/teaching/module-ec968 Downloadable papers and software: http://ideas.repec.org/e/pje7.html Learn about the UK's new household panel survey, "Understanding Society": http://www.understandingsociety.org.uk/ * * 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/

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