epa | R Documentation |
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.
rsadd
,
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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