View source: R/restricted.residual.mean.r
restricted.residual.mean | R Documentation |
The restricted means are the
\int_0^\tau S(t) dt
the standard errors are computed using the i.i.d. decompositions from the cox.aalen (that must be called with the argument "max.timpoint.sim=NULL") or aalen function.
restricted.residual.mean(out, x = 0, tau = 10, iid = 0)
out |
an "cox.aalen" with a Cox model or an "aalen" model. |
x |
matrix with covariates for Cox model or additive hazards model (aalen). |
tau |
restricted residual mean. |
iid |
if iid=1 then uses iid decomposition for estimation of standard errors. |
must have computed iid decomposition of survival models for standard errors to be computed. Note that competing risks models can be fitted but then the interpretation is not clear.
Returns an object. With the following arguments:
mean |
restricted mean for different covariates. |
var.mean |
variance matrix. |
se |
standard errors. |
S0tau |
estimated survival functions on time-range [0,tau]. |
timetau |
vector of time arguments for S0tau. |
Thomas Scheike
D. M. Zucker, Restricted mean life with covariates: Modification and extension of a useful survival analysis method, J. Amer. Statist. Assoc. vol. 93 pp. 702-709, 1998.
Martinussen and Scheike, Dynamic Regression Models for Survival Data, Springer (2006).
### this example runs slowly and is therefore donttest
data(sTRACE)
sTRACE$cage <- scale(sTRACE$age)
# Fits Cox model and aalen model
out<-cox.aalen(Surv(time,status>=1)~prop(sex)+prop(diabetes)+prop(chf)+
prop(vf),data=sTRACE,max.timepoint.sim=NULL,resample.iid=1)
outa<-aalen(Surv(time,status>=1)~sex+diabetes+chf+vf,
data=sTRACE,resample.iid=1)
coxrm <- restricted.residual.mean(out,tau=7,
x=rbind(c(0,0,0,0),c(0,0,1,0),c(0,0,1,1),c(0,0,0,1)),iid=1)
plot(coxrm)
summary(coxrm)
### aalen model not optimal here
aalenrm <- restricted.residual.mean(outa,tau=7,
x=rbind(c(1,0,0,0,0),c(1,0,0,1,0),c(1,0,0,1,1),c(1,0,0,0,1)),iid=1)
with(aalenrm,matlines(timetau,S0tau,type="s",ylim=c(0,1)))
legend("bottomleft",c("baseline","+chf","+chf+vf","+vf"),col=1:4,lty=1)
summary(aalenrm)
mm <-cbind(coxrm$mean,coxrm$se,aalenrm$mean,aalenrm$se)
colnames(mm)<-c("cox-res-mean","se","aalen-res-mean","se")
rownames(mm)<-c("baseline","+chf","+chf+vf","+vf")
mm
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