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#' A simulated dataset with time-invariant longitudinal outcome and covariates.
#'
#' A simulated dataset with time-invariant longitudinal outcome,
#' time-to-event, and time-invariant covariates.
#' Since longitudinal outcome and all of the covariates are time-invariant,
#' there is only one observation per subject.
#' The time-to-event data is right-censored.
#'
#' @format A data frame with 500 rows and 10 variables.
#' \describe{
#' \item{ID}{subject identifier (1 - 500)}
#' \item{X1}{continuous covariate between 0 and 1; time-invariant}
#' \item{X2}{continuous covariate between 0 and 1; time-invariant}
#' \item{X3}{binary covariate; time-invariant}
#' \item{X4}{continuous covariate between 0 and 1; time-invariant}
#' \item{X5}{categorical covariate taking values from {1, 2, 3, 4, 5}; time-invariant}
#' \item{time_Y}{right-censored event time}
#' \item{delta}{censoring indicator, 1 if censored and 0 otherwise}
#' \item{y}{longitudinal outcome; time-invariant}
#' \item{g}{true latent class identifier {1, 2, 3, 4}, which is determined by
#' the outcomes of \eqn{1\{X1 > 0.5\}} and \eqn{1\{X2 > 0.5\}}, with some noise}
#' }
#'
#' @examples
#' # The data for the first five subjects (ID = 1 - 5):
#' #
#' # ID X1 X2 X3 X4 X5 time_Y delta y g
#' # 1 0.27 0.53 1 0.8 1 10.703940 0 0.8923776 2
#' # 2 0.37 0.68 1 0.5 3 9.153915 1 0.6871529 2
#' # 3 0.57 0.38 1 0.2 1 4.489658 1 0.8410745 3
#' # 4 0.91 0.95 0 0.4 3 1.009941 1 2.1058681 4
#' # 5 0.20 0.12 0 0.8 5 11.125094 0 0.1383508 1
#'
#' @docType data
#' @keywords data
#' @name data_timeinv
#' @usage data(data_timeinv)
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