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From |
"Irwin T.S. Wang" <irwintswang@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Question about Baseline Hazard in Parametric Hazard Models |

Date |
Wed, 10 Nov 2010 07:57:00 -0500 |

Paul, Thanks for your information as well. As you pointed out, fitting a model after using -stsplit, at(failures)- on a large data set becomes very slow. I will try your -stmp2 suggestion. Thanks again for your help. TS On Tue, Nov 9, 2010 at 9:21 AM, Lambert, Paul C. (Dr.) <pl4@leicester.ac.uk> wrote: > * > I think Maarten needs to add an -stsplit- to his code before generating the polynomals, i.e. > > sysuse cancer, clear > gen id = _n > stset studytime, failure(died) id(id) > stsplit, at(failures) > orthpoly _t, gen(t*) degree(3) > streg t*, dist(exp) > > However, I agree with both Maarten and Steve that polynomials are not a good way to model the hazard function. Restricted cubic splines are a useful alternative and you could calulate splines rather than polynomials in the above example. However, fitting a model after using -stsplit, at(failures)- on a large data set becomes paintfully slow. If you want to use splines and not have to use -stsplit- then you can use -stpm2- (available from SSC), which models on the log cumulative hazard scale. Below is an example of estimating a hazard function which has a turning point using a restriced cubic splines with 4 knots (3 df). > > > clear > webuse brcancer > stset rectime, f(censrec=1) scale(365.25) exit(time 5*365.25) id(id) > stpm2, scale(hazard) df(3) > predict h, hazard ci > twoway (rarea h_lci h_uci _t, sort pstyle(ci)) (line h _t, sort) > > > Paul > > > Dr Paul C Lambert > Reader in Medical Statistics > Centre for Biostatistics & Genetic Epidemiology > Department of Health Sciences > University of Leicester > 2nd Floor, Adrian Building > University Road > Leicester LE1 7RH > Tel: +44 (0)116 229 7265, Fax: +44 (0)116 229 7250 > e-mail: paul.lambert@le.ac.uk > Homepage: http://www2.le.ac.uk/Members/pl4/ > ________________________________________ > From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of Wei-Kang Shih [wkshih@gmail.com] > Sent: Tuesday, November 09, 2010 1:46 PM > To: statalist@hsphsun2.harvard.edu > Subject: Re: st: Question about Baseline Hazard in Parametric Hazard Models > > Marrten and Steven, > > Thank you both for your suggestions. And yes, the reason I want to > impose a third polynomial baseline hazard is to reproduce some work > done by others. I will try both your suggestion to see what I can get. > > Thanks so much again. > > TS > > On Tue, Nov 9, 2010 at 3:29 AM, Maarten buis <maartenbuis@yahoo.co.uk> wrote: >> --- On Nov 8, 2010, at 5:33 PM, Irwin T.S. Wang wrote: >>> > I would like to specify/estimate a baseline hazard >>> > function, which is not among the distribution provided >>> > by Stata, e.g. exponential, Gompertz, in a Proportional >>> > Hazard (PH) models. For example, I want to restrict the >>> > shape of the the baseline hazard to a third degree >>> > polynomial in time >> >> --- On Tue, 9/11/10, Steven Samuels wrote: >>> Two suggestions: 1) -stpm2- from SSC, which uses >>> restricted cubic splines; and 2) -stcox-, followed by >>> -stcurve-, which will smooth the Cox baseline hazard. I >>> recommend against third degree polynomials, because they can >>> curve up or down at the ends unpredictably and implausibly. >> >> Another option you could investigate is a piecewise constant >> model, see -ssc d stpiece-. >> >> I agree with Steven that such a polynomial would often impose >> too much unrealistic structure on your baseline hazard. The >> only reason I can imagine why you would want use the cubic >> polynomial baseline hazard would be when you want to reproduce >> an analysis made by someone else who used that baseline hazard >> (typically to follow that with a "better" analysis to show >> that they were wrong...). If that is what you want to do, then >> below is an example of how to do that (I used -orthpoly- to >> avoid problems with colinearity): >> >> *-------- begin example --------- >> sysuse cancer, clear >> stset studytime, failure(died) >> orthpoly _t, gen(t*) degree(3) >> streg t*, dist(exp) >> *--------- end example ---------- >> (For more on examples I sent to the Statalist see: >> http://www.maartenbuis.nl/example_faq ) >> >> 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/ >> > > * > * 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/

**References**:**Re: st: Question about Baseline Hazard in Parametric Hazard Models***From:*Steven Samuels <sjsamuels@gmail.com>

**Re: st: Question about Baseline Hazard in Parametric Hazard Models***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**Re: st: Question about Baseline Hazard in Parametric Hazard Models***From:*Wei-Kang Shih <wkshih@gmail.com>

**RE: st: Question about Baseline Hazard in Parametric Hazard Models***From:*"Lambert, Paul C. (Dr.)" <pl4@leicester.ac.uk>

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