coxph
Smoothed hazard estimates for coxph
coxphHaz(object, newdata, n.grid = 300, kernel = "epanechnikov", from,
to, ...)
# S3 method for coxphHaz
print(x, digits=NULL, ...)
# S3 method for coxphHaz
plot(x, xlab="Time", ylab="Hazard", type="l", ...)
# S3 method for coxphHazList
plot(x, xlab="Time", ylab="Hazard", type="l",
col=1:length(x), lty=1, legend.args=list(), ...)
# S3 method for coxphHazList
lines(x, ...)
# S3 method for coxphHaz
as.data.frame(x, row.names=NULL, optional=FALSE, level=0.95, ...)
# S3 method for coxphHazList
as.data.frame(x, row.names=NULL, optional=FALSE, ...)
The coxphHaz
function returns either a class of type
c("coxphHaz","density")
when newdata
has one row or, for multiple rows in
newdata
, a class of type "coxphHazList"
, which is a list of
type c("coxphHaz","density")
.
coxph
object
data-frame with covariates for prediction
the number of grid values for which the hazard is calculated
the kernel used for smoothing
argument for density
. Defaults to the minimum time.
argument for density
. Defaults to the maximum time.
object
argument passed to print.density
graphics argument
graphics argument
graphics argument
graphics argument
graphics argument
level for confidence intervals (default=0.95)
NULL
or a character vector giving the row names for the
data frame. Missing values are not allowed.
logical. If TRUE
, setting row names and converting column
names (to syntactic names: see make.names
) is optional.
Note that all of R's base
package as.data.frame()
methods
use optional
only for column names treatment, basically
with the meaning of data.frame(*, check.names = !optional)
.
See also the make.names
argument of the matrix
method.
a list of options that are passed to the legend call. Defaults are
list(x="topright",legend=strata(attr(x,"newdata")),col=col,lty=lty)
.
other arguments. For coxphHaz
, these arguments are passed to
density
. For the plot
and lines
methods, these are
passed to the relevant plot
, matplot
and matlines
functions.
Smooth hazard estimates from a Cox model using kernel smoothing of the Nelson-Aalen estimator.
fit <- coxph(Surv(surv_mm/12,status=="Dead: cancer")~agegrp, data=colon)
newdata <- data.frame(agegrp=levels(colon$agegrp))
haz <- suppressWarnings(coxphHaz(fit,newdata))
plot(haz, xlab="Time since diagnosis (years)")
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