Combine competing event times — combine_competing

Reduces several latent event times to the one observed first: the observed time is their row-wise minimum and the event code says which process won. Naming one of them in censor turns that process into censoring, so its code is 0 and the remaining processes are coded 1, 2, ... in the order they appear in events. Without censor every row is an event and no code is 0. Ties are broken in favor of the earlier entry of events.

Usage

combine_competing_risks(
  data,
  events,
  censor = NULL,
  time = "time",
  event = "event",
  type = "event_type",
  keep_events = FALSE
)

Arguments

data: Base data.frame, or a simulab_sim, containing the event-time variables, with at least one row.
events: Event-time variable names. A character vector of at least two names, all present in data, holding complete numeric times.
censor: Optional name of the one entry of events that represents censoring rather than an event. A single string, or NULL (the default) when every process is an event.
time: Name of the observed-time variable. A single string, defaulting to "time".
event: Name of the integer event-code variable. A single string, defaulting to "event". The code is 0 for the process named in censor and 1, 2, ... for the other entries of events, in their given order.
type: Name of the character event-type variable, holding the winning process name. A single string, defaulting to "event_type".
keep_events: Retain the component event-time variables. A single flag, defaulting to FALSE, which drops them.

Value

A simulab_sim base data.frame with one row per input row: the columns of data (without the entries of events unless keep_events is TRUE) followed by time, event and type under the names given by those arguments. The component events, reached with as.data.frame(x, what = "events"), is the codebook, one row per process with columns event_type, event_code and the logical censoring.

Examples

data <- data.frame(id = 1:100, treatment = rep(0:1, each = 50))
data <- augment_survival(
  data,
  specification = define_survivals(
    define_survival("time_relapse", formula = -8, shape = 0.3),
    define_survival("time_death", formula = -9, shape = 0.3)
  ),
  seed = 1
)

result <- combine_competing_risks(
  data, events = c("time_relapse", "time_death")
)
head(result)
#> <simulab_sim:competing_risks> 6 rows x 5 columns
#>   id treatment      time event   event_type
#> 1  1         0 11.499102     2   time_death
#> 2  2         0 10.985087     1 time_relapse
#> 3  3         0  9.248955     1 time_relapse
#> 4  4         0  3.406859     2   time_death
#> 5  5         0 11.760588     2   time_death
#> 6  6         0  5.640350     1 time_relapse
#> 
#> Other tables: events. Read one with as.data.frame(x, what = "events").