Re: st: KM curve adjusted by the Inverse Probability of Treatment Weights(IPTW)

[Marcos Vinicius <bioestatistico@inbox.com>]

Thank you Adam.Helped a lot.

> -----Original Message-----
> From: adam.olszewski@gmail.com
> Sent: Thu, 20 Dec 2012 12:31:35 -0500
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: KM curve adjusted by the Inverse Probability of
> Treatment Weights(IPTW)
> 
> Hi Marcos,
> In Stata, you just need to stset your dataset indicating appropriate
> weights:
> stset time [pw=iptw], fail(remission)
> 
> Then you can graph anything you want, and the weight adjustment is
> done automatically:
> sts graph, by(tx)
> 
> I'm not going into the intricacies of what such graphs might or might
> not represent, since I trust you understand them. Curve comparison can
> be only done with a Cox regression (or another regression model if you
> prefer, such as Royston-Parmar). You will not be able to use the efron
> or exact tie adjustment.
> 
> sts test tx
> which should be the same as
> stcox test
> 
> I am not a statistician and do not understand very well why/if
> non-parametric tests can or cannot be done with pweighted data, but
> simple logrank certainly cannot be done and Stata will refuse to
> perform it (it will default to Cox). On the other hand, the
> -stpepemori- (available through SSC) command from Enzo Coviello works
> in a pweighted dataset and I had at least one expert declare that it
> should be valid to use. If any of our statisticians on the list can
> (p)weigh in on the subject I would be delighted to hear!
> 
> Great reference:
> Cole, S. R. and M. A. Hernan (2004). "Adjusted survival curves with
> inverse probability weights." Comput Methods Programs Biomed 75(1):
> 45-49.
> And of course the famous:
> Hernan, M. A., et al. (2000). "Marginal structural models to estimate
> the causal effect of zidovudine on the survival of HIV-positive men."
> Epidemiology 11(5): 561-570.
> 
> Adam Olszewski
> 
> On Thu, Dec 20, 2012 at 11:55 AM, Marcos Vinicius
> <bioestatistico@inbox.com> wrote:
>> Hello,
>> I would like to generate a Kaplan Meier curve
>> adjusted(controlled/corrected) by the Inverse Probability of Treatment
>> Weights(IPTW).
>> Supose I have a dataset with columns: tx=treatment (0/1)  ,
>> ps=propensity score weig=  Inverse Probability of Treatment Weights
>> (iptw),time (=survival time)remission(1/0) (0=censored),
>> In IPTW, individuals are weighted by the inverse probability of
>> receiving the treatment that they actually received.
>> In SAS I tried this code but it is not working although it is indicated
>> in the SAS/STAT
>> 12.1 User’s Guide The LIFETEST Procedure (Chapter)
>> Someone could help me with a Stata code to produte and compare 2 Km
>> curves according to treatment group but adjusted by iptw(weig)
>> proc lifetest method=km data=ps plots = (survival );
>> 
>> time time*remission(0);
>>  weight weig;
>> survival out=surv_data conftype=loglog ;
>> /*weight weig;*/
>> ODS EXCLUDE ProductLimitEstimates Means LogrankHomCov WILHOMCOV HomStats
>> TaroneHomCov PetoHomCov Rank HomTests  ;
>> /*weight weig;*/
>> strata tx;
>> /*weight weig;*/
>>  run;
>> [
>> Error message from SAS log
>> ERROR 180-322: Statement is not valid or it is used out of
>>                proper order.
>> 
>> 
>> After program the  propensity score weight , also referred to as the
>> inverse probability oftreatment weight (IPTW)( weig in the  SAS code) I
>> tried to use the weight statatement from proc Lifetest to produce a
>> Kaplan-Meier curve adjusted by iptw. It is not working.
>> Someone could help me in the code implementation  or guide another way
>> to produce the KM curve adjusted by propensity score?:
>> Many thanks,
>> Vinicius.
>> 
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