Thanks Prof. Terry for the response. To answer the second comment, the weights I am considering are inverse probability of treatment weights (IPTW). To perform bootstrapping, my initial thought would be to - select patients (sampling from unique id with replacement) and - then include all the multiple observations of the selected patients (include all rows with the selected id) to make a bootstrap sample. - Then create new weights based on this bootstrap sample (I mean, based on covariate history of the selected patients) and - then run the stated weighted Cox model with this bootstrap sample. This should give me point estimate (of treatment effect or HR) from one sample. Similarly I would repeat for all bootstrap samples. My question is: does this bootstrap strategy sound reasonable? I am guessing boot() can be used here once the above is put in a function.
Any suggestions/references will be highly appreciated. cheers, Ehsan On Tue, Feb 21, 2012 at 11:11, Ehsan Karim <wilds...@hotmail.com> wrote: > > >> Subject: Re: bootstrap in time dependent Cox model? >> From: thern...@mayo.edu >> To: wilds...@hotmail.com >> CC: r-help@r-project.org >> Date: Tue, 21 Feb 2012 07:06:16 -0600 >> >> Two comments. >> I've not found bootstrapping worthwhile for Cox models. If one has >> 10-20 events per covariate and no outrageous coefficients (risks of >10 >> fold) the standard asymptotics are very good. With an multiple events >> AG model there is the additional consideration that no one subject is >> responsible for too many of the events. (Years ago I was working on a >> study of recurrent syncope in Long QT syndrome. Most subjects had 0 >> events, some 1, and one gentleman 29. The multi-event analysis could be >> summarized as "don't look like him.") >> >> I like to think of bootstrapping in two stages. First, the "best" >> answer which is what I would get if I had enough money to repeat the >> study 100 times. Then set up the bootstrap to resemble that. In your >> case, what would the pattern of weights be in the hypothetical repeat? >> For instance, if your weights are sampling weights from a structured >> design, the repeat might have the same set of weights and creating a >> bootstrap strategy to replicate it will be more challenging. >> >> Terry T. >> >> ---- begin included message ---- >> >> I am wondering how to perform a bootstrap in R for the weighted time >> dependent Cox model? (Andersen?Gill format, with multiple observations >> from each patients) to obtain the bootstrap standard error of the >> treatment effect. >> >> ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
