Excess hazard function smoothing
An Epanechnikov kernel function based smoother for smoothing the baseline excess hazard calculated by the rsadd function with the EM method.
epa(fit,bwin,times,n.bwin=16,left=FALSE)
fit |
Fit from the additive relative survival model using the |
bwin |
The relative width of the smoothing window (default is 1). |
times |
The times at which the smoother is to be evaluated. If missing, it is evaluated at all event times. |
n.bwin |
Number of times that the window width may change. |
left |
If |
The function performs Epanechnikov kernel smoothing. The follow up time is divided (according to percentiles of event times) into several intervals (number of intervals defined by n.bwin) in which the width is calculated as a factor of the maximum span between event times.
Boundary effects are also taken into account on both sides.
A list with two components:
lambda |
the smoothed excess baseline hazard function |
times |
the times at which the smoothed excess baseline hazard is evaluated. |
Package. Pohar M., Stare J. (2006) "Relative survival analysis in R." Computer Methods and Programs in Biomedicine, 81: 272–278
Relative survival: Pohar, M., Stare, J. (2007) "Making relative survival analysis relatively easy." Computers in biology and medicine, 37: 1741–1749.
EM algorithm: Pohar Perme M., Henderson R., Stare, J. (2009) "An approach to estimation in relative survival regression." Biostatistics, 10: 136–146.
data(slopop) data(rdata) #fit an additive model with the EM method fit <- rsadd(Surv(time,cens)~sex+age,rmap=list(age=age*365.241), ratetable=slopop,data=rdata,int=5,method="EM") sm <- epa(fit) plot(sm$times,sm$lambda)
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