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From |
"Justin B Echouffo Tcheugui" <jbe24@medschl.cam.ac.uk> |

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

Subject |
RE: st: Multilevel modelling of survival data |

Date |
Wed, 25 Mar 2009 15:17:57 -0000 |

Dear Marteen, I am using the population averaged Cox model in my analysis of clustered data form a trial: stcox with the option-cluster (). Not being in possession of the book you advised, I thought that I could ask you another question. The marginal (Cox) model uses the sandwich estimator to obtain standard errors. It seems that with a total number of clusters below 40 as it is my case, one has to correct the confidence interval as with less than 40 clusters the sandwich estimator is biased downwards. I am not sure about how to correct for the confidence intervals in general and in Stata in particular. How do I do that in Stata? I came across an article suggesting theoretical approaches (use of a t distribution or jacknife standard errors) to do the correction, but it does not really tell how to implement the suggested approaches in a package. What about the following ways of implementing the approaches below? 1- Using the t distribution instead of the Z distribution to derive CI: Would the derivation of the confidence interval using the robust SE on the log scale and the value of the t distribution with n-2 degree of freedom instead of the usual 1.96 value, where n is the total number of clusters randomised, be a sensible approach? I would then do and exponentiation of the CI limits to have the corrected standard errors. I am thinking of something like this: Estimates ± t30 x robust SE on the log scale. Does that sounds like a sensible application of this correction. 2- Using a jacknife estimator instead of the sandwich estimator: xi: jacknife: stcox i.randomgp, cluster(clinic) What do you think? I hope that I am not completely off track Many thanks Justin B. -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Justin B Echouffo Tcheugui Sent: 16 March 2009 16:17 To: statalist@hsphsun2.harvard.edu Subject: RE: st: Multilevel modelling of survival data Dear Marteen, I tried the command stcox with the option -shared () as you advised. As you can see below I am not having the desired output xi: stcox i.randomgp, shared(clinic) i.randomgp _Irandomgp_0-1 (naturally coded; _Irandomgp_0 omitted) failure _d: event analysis time _t: followup_time Fitting comparison Cox model: Estimating frailty variance: numerical derivatives are approximate flat or discontinuous region encountered Iteration 0: log profile likelihood = -2482.4152 could not calculate numerical derivatives flat or discontinuous region encountered r (430); I tried adding the option - difficult, hoping that it will help but it did not xi: stcox i.randomgp, shared(practice) difficult i.randomgp _Irandomgp_0-1 (naturally coded; _Irandomgp_0 omitted) failure _d: event analysis time _t: followup_time Fitting comparison Cox model: Estimating frailty variance: numerical derivatives are approximate flat or discontinuous region encountered Iteration 0: log profile likelihood = -2482.4152 could not calculate numerical derivatives flat or discontinuous region encountered r(430); Could you please advise on this? Many thanks Justin B. -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Maarten buis Sent: 16 March 2009 10:58 To: stata list Subject: RE: st: Multilevel modelling of survival data --- On Mon, 16/3/09, Justin B Echouffo Tcheugui wrote: > > in this case the option - cluster() in this case does > > not fit the clinic into the model as a random > > intercept --- On Mon, 16/3/09, Maarten buis wrote: > That is correct. A point on terminology again: When discussing the distrinction between these models, the models estimated with the -cluster()- option are sometimes known as population averaged models, while the random intercept models are sometimes known as individual specific models. -- Maarten ----------------------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://home.fsw.vu.nl/m.buis/ ----------------------------------------- * * 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: Multilevel modelling of survival data***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**RE: st: Multilevel modelling of survival data***From:*"Justin B Echouffo Tcheugui" <jbe24@medschl.cam.ac.uk>

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