coxph2WR {oceCens} | R Documentation |
Take coxph object and translate results to win ratios.
Description
Let cout
a coxph object, then Using normal approximations and the output from the
cout$coefficients
and cout$var
. If the cluster argument is used in the coxph
call, then cout$var
is the robust variance (see coxph
.
Usage
coxph2WR(coutput, conf.level = 0.95)
Arguments
coutput |
a coxph object created by |
conf.level |
confidence level. |
Details
The function takes a beta coefficient and returns the win ratio version: exp(-beta). Confidence intervals are calculated by exp(-beta -/+ qnorm(1-(1-conf.level)/2)*sqrt(coutput$var)). P-values are two-sided.
Value
A vector or matrix with 4 elements (or columns) giving the win ratio, the lower and upper confidence limits, and the two-sided p-value.
References
Follmann, D., Fay, M. P., Hamasaki, T., and Evans, S. (2020). Analysis of ordered composite endpoints. Statistics in Medicine, 39(5), 602-616.
Examples
data(simScenario5)
xform<-oceFormat(data=simScenario5,oceTime=c("T1","T2","T3"),
oceStatus=c("I1","I2","I3"),
group="Z",outputDataFrame=TRUE)
# perform cox regression using time varying treatment efects, IZ1,IZ2, IZ3
# associated with the 3 prioritized endpoints
cout<- coxph(Surv(START, STOP, status) ~ IZ1+IZ2+IZ3, data=xform$data)
coxph2WR(cout)