Re: [R] How do I specify a partially completed survival analysis model?
Sorry for being impatient but is there really no way of doing this at all? It's quite urgent so any help is very much appreciated. Thank you. RWilliam wrote: Hello, I just started using R to do epidemiologic simulation research using the Cox proportional hazard model. I have 2 covariates X1 and X2 which I want to model as h(t,X)=h0(t)*exp(b1*X1+b2*X2). I assume independence of X from t. After I simulate Time and Censor data vectors denoting the censoring time and status respectively, I can call the following function to fit the data into the Cox model (a is a data.frame containing 4 columns X1, X2, Time and Censor): b = coxph (Surv (Time, Censor) ~ X1 + X2, data = a, method = breslow); Now the purpose of me doing simulation is that I have another mechanism to generate the number b2. From the given b2 (say it's 4.3), Cox model can be fit to generate b1 and check how feasible the new model is. Thus, my question is, how do I specify such a model that is partially completed (as in b2 is known). I tried things like Surv(Time,Censor)~X1+4.3*X2, but it's not working. Thanks very much. -- View this message in context: http://old.nabble.com/How-do-I-specify-a-partially-completed-survival-analysis-model--tp26421391p26441878.html Sent from the R help mailing list archive at Nabble.com. __ 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.
Re: [R] How do I specify a partially completed survival analysis model?
In reply to suggestion by David W., setting an offset parameter doesn't seem to work as R is not recognizing the X2 part of coxph( Surv(Time,Censor)~X1, offset=log(4.3*X2), data= a ). Also, here's some sample data: X1 X2 TimeCensor 1 1 0.40619454 77.00666 0 2 1 0.20717868 100.0 0 3 1 0.77360963 79.03463 1 4 1 0.62221954 100.0 0 5 1 0.32191280 100.0 0 6 1 0.73790704 72.84842 0 7 1 0.65012237 100.0 0 8 1 0.71596105 100.0 0 9 1 0.74787202 84.00172 0 10 1 0.66803790 41.65760 0 11 1 0.79922364 92.41999 0 12 1 0.76433736 90.99983 0 13 1 0.57014524 100.0 0 14 1 0.39642235 100.0 0 15 1 0.55756045 100.0 0 16 0 0.60079340 100.0 0 17 0 0.43630695 100.0 0 18 0 0.09388013 100.0 0 19 0 0.55956791 100.0 0 20 0 0.52491597 97.71884 1 where we set the coefficient of X2 to be 8. RWilliam wrote: Sorry for being impatient but is there really no way of doing this at all? It's quite urgent so any help is very much appreciated. Thank you. RWilliam wrote: Hello, I just started using R to do epidemiologic simulation research using the Cox proportional hazard model. I have 2 covariates X1 and X2 which I want to model as h(t,X)=h0(t)*exp(b1*X1+b2*X2). I assume independence of X from t. After I simulate Time and Censor data vectors denoting the censoring time and status respectively, I can call the following function to fit the data into the Cox model (a is a data.frame containing 4 columns X1, X2, Time and Censor): b = coxph (Surv (Time, Censor) ~ X1 + X2, data = a, method = breslow); Now the purpose of me doing simulation is that I have another mechanism to generate the number b2. From the given b2 (say it's 4.3), Cox model can be fit to generate b1 and check how feasible the new model is. Thus, my question is, how do I specify such a model that is partially completed (as in b2 is known). I tried things like Surv(Time,Censor)~X1+4.3*X2, but it's not working. Thanks very much. -- View this message in context: http://old.nabble.com/How-do-I-specify-a-partially-completed-survival-analysis-model--tp26421391p26443562.html Sent from the R help mailing list archive at Nabble.com. __ 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.
[R] How do I specify a partially completed survival analysis model?
Hello, I just started using R to do epidemiologic simulation research using the Cox proportional hazard model. I have 2 covariates X1 and X2 which I want to model as h(t,X)=h0(t)*exp(b1*X1+b2*X2). I assume independence of X from t. After I simulate Time and Censor data vectors denoting the censoring time and status respectively, I can call the following function to fit the data into the Cox model (a is a data.frame containing 4 columns X1, X2, Time and Censor): b = coxph (Surv (Time, Censor) ~ X1 + X2, data = a, method = breslow); Now the purpose of me doing simulation is that I have another mechanism to generate the number b2. From the given b2 (say it's 4.3), Cox model can be fit to generate b1 and check how feasible the new model is. Thus, my question is, how do I specify such a model that is partially completed (as in b2 is known). I tried things like Surv(Time,Censor)~X1+4.3*X2, but it's not working. Thanks very much. -- View this message in context: http://old.nabble.com/How-do-I-specify-a-partially-completed-survival-analysis-model--tp26421391p26421391.html Sent from the R help mailing list archive at Nabble.com. __ 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.
