Re: st: R: Estimating the probability of censoring

[Michael McCulloch <mm@pinest.org>]

Works perfectly; thanks Nick!

> The UCLA example is using old-style -graph syntax- for Stata <8.
>
> You need something more like
>
> twoway line surv1 surv2, c(J ..) sort <etc.>
>
> Nick
> n.j.cox@durham.ac.uk
>
> Michael McCulloch wrote:
>
> > Antoine, thank you also for pointing out that example web page.
> > I attempt to re-create their graph using
> >     graph surv1 surv2, s(..) c(JJ) sort ylab(0 .1 to 1) xlab(0 200 to 1200)
> > but receive the error message:
> > "surv1graph_g.new surv2, s(..) c(JJ) sort ylab(0 .1 to 1) xlab(0 
> > 200 to 1200): class member
> >     function not found"
> >
> > I'm using v9.2. Might that be the problem?
> > Michael
> >
> >
> >
> >
> > > using predicted baseline survival function sounds like a better 
> > > idea (from 
> > > http://www.ats.ucla.edu/stat/stata/seminars/stata_survival/default.htm#graphs) 
> > > :
> > >
> > > stcox drug age, nohr  bases(surv0)
> > > gen cens_adj2=surv0^(exp(coeff_cens))
> > >
> > > list id drug age died cens p_cens cens_adj2 in 40/48, clean noobs
> > >
> > >
> > >     id   drug   age   died        cens     p_cens   cens_a~2
> > >     40      3    50      0   .58476475   .8601028   .6717925
> > >     41      3    55      1   .58476475   .9429854   .6465274
> > >     42      3    57      1   .51166915   .9783332   .5577559
> > >     43      3    48      0   .51166915   .8290267   .6097336
> > >     44      3    56      0   .34111277   .9604967   .3796235
> > >     45      3    60      1   .34111277   1.033855   .3525544
> > >     46      3    62      0   .22740851   1.072609   .2088839
> > >     47      3    48      0   .11370426   .8290267   .1545282
> > >     48      3    52      0           0   .8923438          0
> > >
> > >
> > > Antoine Terracol wrote:
> > > > I might be missing something, but isn't the correct way to do 
> > > > this more like (the part where I generate cens_adj):
> > > >
> > > > sysuse cancer.dta, clear
> > > > gen id = _n                //  generate individual IDs
> > > > stset studytime, failure(died==0)        //  note that total 
> > > > person-time is 744
> > > > *estimate the unadjusted probability of censoring
> > > > sts gen cens = s
> > > > *estimate the adjusted probability of censoring
> > > > stcox drug age, nohr basec(cum)
> > > > predict coeff_cens, xb            // predicts linear coefficients 
> > > > of censoring
> > > > gen p_cens = exp(coeff_cens)        // adjusted probability of 
> > > > time-to-censoring
> > > >
> > > > gen cens_adj=exp(-cum*exp(coeff_cens))
> > > >
> > > > *lists the results
> > > >
> > > > list id drug age died cens p_cens cens_adj in 40/48, clean noobs
> > > >
> > > >
> > > >     id   drug   age   died        cens     p_cens   cens_adj
> > > >     40      3    50      0   .58476475   .8601028   .6811302
> > > >     41      3    55      1   .58476475   .9429854   .6563864
> > > >     42      3    57      1   .51166915   .9783332   .5705886
> > > >     43      3    48      0   .51166915   .8290267   .6216006
> > > >     44      3    56      0   .34111277   .9604967   .4199265
> > > >     45      3    60      1   .34111277   1.033855   .3930005
> > > >     46      3    62      0   .22740851   1.072609   .2585016
> > > >     47      3    48      0   .11370426   .8290267   .2171345
> > > >     48      3    52      0           0   .8923438   .0710848
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