curelps.extract {blapsr} | R Documentation |
Extract estimates of survival functions and cure probability for the promotion time cure model.
Description
The routine takes as input an object of class curelps
and computes
estimates of the baseline survival curve, the population survival
curve and the cure probability on a specified time vector. Approximate
pointwise credible intervals are available.
Usage
curelps.extract(object, time = NULL, curvetype = c("baseline", "population", "probacure"),
covar.profile, compute.cred = TRUE, cred.int = 0.95, verbose = TRUE)
Arguments
object |
An object of class |
time |
A vector of time values on which to compute the estimates.
Each component of |
curvetype |
The curve on which estimates are computed ; |
covar.profile |
A numeric vector of the same length as the number
of covariates in the model. This corresponds to the profile of covariates
for which to compute the population survival function and cure probability
estimates. The order of the covariates in |
compute.cred |
Should credible intervals be computed? Default is TRUE. |
cred.int |
The level for an approximate pointwise credible interval. Default is 0.95. |
verbose |
Should estimates be printed to console? |
Value
A list with the following components:
fit.time |
Estimates on the time values provided in |
cred.int |
The chosen level to construct approximate pointwise credible intervals. |
covar.profile |
The chosen profile of covariates. |
Author(s)
Oswaldo Gressani oswaldo_gressani@hotmail.fr.
See Also
curelps
, curelps.object
,
plot.curelps
, print.curelps
.
Examples
# Example on phase III clinical trial e1684 on melanoma data
data(ecog1684)
# Kaplan-Meier curve
plot(survfit(Surv(time, status) ~ 1, data = ecog1684), mark.time = TRUE)
fit <- curelps(Surv(time, status) ~ lt(age + trt+ sex) +
st(age + trt + sex), data = ecog1684, K = 20, penorder = 2)
fit
profile1 <- c(0, 1, 1, 0, 1, 1) # Mean age, trt = IFN, sex = Female.
profile2 <- c(0, 0, 1, 0, 0, 1) # Mean age, trt = control, sex = Female.
# Extract cure probabilities
curelps.extract(fit, time = c(0, 1, 2, 3), curvetype = "probacure",
covar.profile = profile1, cred.int = 0.90)
curelps.extract(fit, time = c(0, 1, 2, 3), curvetype = "probacure",
covar.profile = profile2, cred.int = 0.90)