Cumulative incidence surface over two time scales

Usage

cuminc2ts(haz = list(), ds, cause = NULL)

Arguments

haz: a list of cause-specific hazards
ds: the distance between two consecutive intervals over the s time scale. This has to be equal for all cause-specific hazards
cause: is an optional vector of short names for the causes. It should be of the same length as the number of cause-specific cumulated hazards provided.

Value

a list with one cumulative incidence matrix for each cause-specific hazard (named if a vector of short names is passed to cause).

Examples

# Create some fake data - the bare minimum
id <- 1:20
u <- c(5.43, 3.25, 8.15, 5.53, 7.28, 6.61, 5.91, 4.94, 4.25, 3.86, 4.05, 6.86,
       4.94, 4.46, 2.14, 7.56, 5.55, 7.60, 6.46, 4.96)
s <- c(0.44, 4.89, 0.92, 1.81, 2.02, 1.55, 3.16, 6.36, 0.66, 2.02, 1.22, 3.96,
       7.07, 2.91, 3.38, 2.36, 1.74, 0.06, 5.76, 3.00)
ev <- c(1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1)#'

fakedata <- as.data.frame(cbind(id, u, s, ev))
fakedata2ts <- prepare_data(u = fakedata$u,
                            s_out = fakedata$s,
                            ev = fakedata$ev,
                            ds = .5)
#> `s_in = NULL`. I will use `s_in = 0` for all observations.
#> `s_in = NULL`. I will use `s_in = 0` for all observations.
# Fit a fake model - not optimal smoothing
fakemod <- fit2ts(fakedata2ts,
                  optim_method = "grid_search",
                  lrho = list(seq(1 ,1.5 ,.5),
                              seq(1 ,1.5 ,.5)))

# Obtain the fake cumulated hazard
fakecumhaz2ts <- cumhaz2ts(fakemod)
# Fake cumulative incidence function 2ts
fakecif2ts <- cuminc2ts(haz = list(fakecumhaz2ts$Haz$hazard),
                        ds = .5)