Description Usage Arguments Details Value Author(s) References Examples
This function is used to obtain nonparametric estimates of the cumulative incidence probabilities in the illnessdeath model. They represent the probability of one individual's being or having been in state j at time t.
1 2 3 
formula 
A 
s 
The first time for obtaining estimates for the cumulative incidence functions. If missing, 0 will be used. 
data 
A data.frame including at least four columns named

conf 
Provides pointwise confidence bands. Defaults to 
n.boot 
The number of bootstrap replicates to compute the variance of the estimator. Default is 199. 
conf.level 
Level of confidence. Defaults to 0.95 (corresponding to 95%). 
z.value 
The value of the covariate on the right hand side of formula at which the cumulative incidence probabilities are computed. For quantitative covariates, i.e. of class integer and numeric. 
bw 
A single numeric value to compute a kernel density bandwidth.
Use 
window 
A character string specifying the desired kernel.
See details below for possible options. Defaults to 
method.weights 
A character string specifying the desired weights method.
Possible options are 
cluster 
A logical value. If 
ncores 
An integer value specifying the number of cores to be used in
the parallelized procedure. If 
presmooth 
A logical value. If 
Possible options for argument window are "gaussian"
,
"epanechnikov"
, "tricube"
, "boxcar"
,
"triangular"
, "quartic"
or "cosine"
.
An object of class "survIDM"
and one of the following
two classes: "CIF"
(Cumulative Incidence Function), and
"cifIPCW"
(Inverse Probability of Censoring Weighting for the Cumulative Incidence Function). Objects are implemented as a list with elements:
est 
data.frame with estimates of the cumulative incidence probabilities. 
CI 
data.frame with the confidence intervals of the cumulative incidence probabilities. 
conf.level 
Level of confidence. 
s 
The first time for obtaining estimates for the cumulative incidence probabilities. 
t 
The time for obtaining the estimates of cumulative incidence probabilities. 
conf 
logical; if 
callp 
The expression of the estimated probability. 
Nlevels 
The number of levels of the covariate. Provides important information when the covariate at the right hand side of formula is of class factor. 
levels 
The levels of the qualitative covariate (if it is of class factor) on the right hand side of formula. 
formula 
A formula object. 
call 
A call object. 
Luis MeiraMachado, Marta Sestelo and Gustavo Soutinho.
Geskus, R.B. (2011). Causespecific cumulative incidence estimation and the fine and gray model under both left truncation and right censoring. Biometrics, 67, 39–49.
Kalbeisch, J. D. and Prentice R. L. (1980) The statistical analysis of failure time data. John Wiley & Sons, New York.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38  # Cumulative Incidence Function (CIF)
res < CIF(survIDM(time1, event1, Stime, event) ~ 1, data = colonIDM,
conf = FALSE)
res
summary(res, time=365*1:7)
plot(res, ylim=c(0, 0.6))
res01 < CIF(survIDM(time1, event1, Stime, event) ~ 1, data = colonIDM,
conf = FALSE, presmooth = TRUE)
res01
summary(res01, time=365*1:7)
plot(res01, ylim=c(0, 0.6))
# CIF for those in State 1 at time s=365, Y(s)=0
res1 < CIF(survIDM(time1, event1, Stime, event) ~ 1, data = colonIDM,
s = 365, conf = FALSE)
summary(res1, time=365*1:7)
plot(res1, ylim=c(0, 0.6))
# Conditional CIF (with a factor)
res2 < CIF(survIDM(time1, event1, Stime, event) ~ factor(sex),
data = colonIDM, s = 365, conf = FALSE)
summary(res2, time=365*1:5)
plot(res2)
res2.1 < CIF(survIDM(time1, event1, Stime, event) ~ factor(sex), #new
data = colonIDM, s = 365, conf = FALSE, presmooth = TRUE)
summary(res2.1, time=365*1:5)
plot(res2.1)
# Conditional CIF (with continuous covariate)
res3 < CIF(survIDM(time1, event1, Stime, event) ~ age, data = colonIDM,
z.value = 56, conf = FALSE)
summary(res3, time=365*1:6)
plot(res3)

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