| cif {surv2sample} | R Documentation |
Compute estimates of cumulative incidence functions for one or more samples of censored data with several competing risks (types of failure).
cif(x, group)
x |
an object of class "Survcomp". |
group |
a vector giving for each observation the group
to which the observation belongs. If there are K samples,
group may only contain values 1,...,K.
If group is missing, observations are assumed to be
one sample. |
The cumulative incidence function F(t,j) is defined as the probability of failure by time t from a particular cause j in the presence of other competing risks 1,...,j-1,j+1,...,J, that is, F(t,j)=P(T<=t, e=j), where T is the failure time and e is the failure cause.
The function cif estimates cumulative incidence functions for
all causes and all groups.
cif returns a list of class "cif" with the following components:
[[k]] |
a list containing estimates for the kth
sample. It has components time (sorted times in the
group k), surv (the Kaplan–Meier estimate of the
overall survival in this group), and f, which is
a matrix containing estimates of cumulative incidence functions
for the kth sample. The jth column of f is
the cumulative incidence function for the cause j. |
time |
the vector of sorted times. |
event |
the vector of corresponding event types. |
group |
the vector of corresponding group indicators. |
ncauses |
the number of causes present in the data. |
ngroups |
the number of samples. |
David Kraus (http://www.davidkraus.net/)
Klein, J. P. and Moeschberger, M. L. (2003) Survival Analysis. Techniques for Censored and Truncated Data. Springer, New York. (Section 2.7)
## bone marrow transplant data data(bmt1) print(a <- cif(Survcomp(bmt1$time, bmt1$event), bmt1$donor)) str(a) ## several first times and cifs for group 1 (HLA-identical ## sibling donors) head(cbind(a[[1]]$time, a[[1]]$f)) ## several last times and cifs for group 2 (HLA-matched ## unrelated donors) tail(cbind(a[[2]]$time, a[[2]]$f)) ## plot aggregate cumulative incidence functions for each ## donor type to see probabilities within groups plot(a)