Description Usage Arguments Value Author(s) See Also Examples
'pssm' fits a proportional hazards model where the underlying hazard of time to progression and subsequent survival are both piecewise constant. The hazard from progression to death is different for each interval for which the hazard of progression is constant. The covariates for progression and death after progression may be different. Time to progression is interval censored while time to death is right censored. Patients who die must have a progression interval with a right endoint that is at or before the death time.
1 |
progr |
a formula object of the form Surv(time0,time1)~covariates for the time to progression, if NULL it fits a piecewise exponential model for survival time only. The progression time is assumed to be interval censored between time0 and time1. If progression does not occur then time1=NA. |
survv |
a formula object of the form Surv(time,cns)~covariates for time from progression to death, if NULL a model for time to progression is fit. The code for "cns" is 1=dead, 0=alive. |
dat |
A data frame with the data used in the estimation |
intervals |
An integer indicating the number of intervals in the time to progression or survival model. If both progr and survv are present than intervals is the number of intervals for the progession model. The survival model will have intervals*(intervals+1)/2 hazard parameters. If the model doesn't converge the number of intervals will be reduced by the program until convergence occurs. |
start |
starting values for the parameter vector, suppose |
rescale |
A number that will multiply the survival and progression times before processing. This will be changed by the program if the maximum survival or progression time is greater than m r. |
prior |
A vector of prior values for the covariates affecting the hazards, set to 0 if NULL. |
An S4 pssm.object
containing the estimated parameters, their standard errors,
their variance covariance matrix, and details of the model that was fit. The generic functions plot, summary and print are defined for the object.
David A. Schoenfeld
pssm-class
,
pssm-package
,
pssm.generate.data
,
pssm.object
,
pssm.simulate
,
pssm.survivalcurv
,
plot-methods
,
pssm.power
pssm.noninferiority.boundary
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
#generate data
set.seed(359)
u<-pssm.generate.data(theta1=.5,theta2=0,phaz.progression=rep(log(-log(.3)/4),5),
phaz.survival=rep(log(-log(.2)/4),15),accrual=2,followup=2.9,m=5,n=100,times=c(.8,2.1,3.4))
#estimate based on joint model
ps<-pssm(surv(tprog0,tprog1)~rx,surv(tdeath,cdeath)~rx,u,intervals=3,rescale=1)
summary(ps)
plot(ps,type='survival',cov1=matrix(c(1,0),2,1),cov2=matrix(c(1,0),2,1))
plot(ps)
plot(ps,type='progression',cov1=matrix(c(1,0),2,1),cov2=matrix(c(1,0),2,1))
#estimate time to progression only (tumor free survival)
ps1=pssm(surv(tprog0,tprog1)~rx,NULL,u,intervals=3,rescale=1)
summary(ps1)
plot(ps1)
plot(ps1,type='progression',cov1=matrix(c(1,0),2,1),cov2=matrix(c(1,0),2,1))
#estimate survival only
ps2=pssm(NULL,surv(tdeath,cdeath)~rx,u,intervals=3,rescale=1)
summary(ps2)
plot(ps2)
plot(ps2,type='survival',cov1=matrix(c(1,0),2,1),cov2=matrix(c(1,0),2,1))
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