sampleCaseBase {casebase} | R Documentation |
This function implements the case-base sampling approach described in Hanley and Miettinen (2009). It can be used to fit smooth-in-time parametric functions easily via logistic regression.
sampleCaseBase( data, time, event, ratio = 10, comprisk = FALSE, censored.indicator )
data |
a data.frame or data.table containing the source dataset. |
time |
a character string giving the name of the time variable. See Details. |
event |
a character string giving the name of the event variable. See Details. |
ratio |
Integer, giving the ratio of the size of the base series to that of the case series. Defaults to 10. |
comprisk |
Logical. Indicates whether we have multiple event types and that we want to consider some of them as competing risks. |
censored.indicator |
a character string of length 1 indicating which
value in |
The base series is sampled using a multinomial scheme: individuals are sampled proportionally to their follow-up time.
It is assumed that data
contains the two columns corresponding to the
supplied time and event variables. If either the time
or event
argument is missing, the function looks for columns with appropriate-looking
names (see checkArgsTimeEvent
).
The function returns a dataset, with the same format as the source dataset, and where each row corresponds to a person-moment sampled from the case or the base series.
The offset is calculated using the total follow-up time for
all individuals in the study. Therefore, we need time
to be on the
original scale, not a transformed scale (e.g. logarithmic). Otherwise, the
offset and the estimation will be wrong.
# Simulate censored survival data for two outcome types from exponential library(data.table) set.seed(12345) nobs <- 500 tlim <- 10 # simulation parameters b1 <- 200 b2 <- 50 # event type 0-censored, 1-event of interest, 2-competing event # t observed time/endpoint # z is a binary covariate DT <- data.table(z = rbinom(nobs, 1, 0.5)) DT[, `:=`( "t_event" = rweibull(nobs, 1, b1), "t_comp" = rweibull(nobs, 1, b2) )] DT[, `:=`( "event" = 1 * (t_event < t_comp) + 2 * (t_event >= t_comp), "time" = pmin(t_event, t_comp) )] DT[time >= tlim, `:=`("event" = 0, "time" = tlim)] out <- sampleCaseBase(DT, time = "time", event = "event", comprisk = TRUE)