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##############################
### Desciption of datasets ###
##############################
#' simulated_data_norm
#'
#' @format ## `simulated_data_norm`
#' A simulated data frame with 600 rows and 8 columns, following a combination of normal and binomial distribution
#' \describe{
#' \item{type}{type of data}
#' \item{y}{result of the model y = x1 + x2 + x3}
#' \item{x1, x2, x3}{random numbers from rnorm}
#' \item{class}{original class of the data point}
#' \item{id}{id number of observations to simulated different persons}
#' \item{y_cens}{column y censored at 3}
#' ...
#' }
#' @source {simulated with true parameter values:
#' Class 1: sigma = 1.0, theta = 5 and c(x1,x2,x3) = c(0.5, -0.3, 0.8)
#' Class 2: sigma = 0.5, theta = 2 and c(x1,x2,x3) = c(1.4, 2.3, -0.2)}
"simulated_data_norm"
#' simulated_data_mo
#'
#' @format ## `simulated_data_mo`
#' A simulated data frame with 480 rows and 9 columns, following a combination of normal and binomial distribution
#' \describe{
#' \item{type}{type of data}
#' \item{y}{result of the model y = -1 + mo2 + mo3 + mo4 + mo5}
#' \item{mo2, mo3, mo4, mo5}{dummy variables}
#' \item{class}{original class of the data point}
#' \item{id}{id number of observations to simulated different persons}
#' \item{y_cens}{column y censored at 0 (lower boundary)}
#' ...
#' }
#' @source {simulated with true parameter values:
#' Class 1: sigma = XXX, theta = XXX and c(mo2,mo3,mo4,mo5) = c(XXX)
#' Class 2: sigma = XXX, theta = XXX and c(mo2,mo3,mo4,mo5) = c(XXX)}
"simulated_data_mo"
#' simulated_data
#'
#' @format ## `simulated_data`
#' A simulated data frame with 480 rows and 25 columns, following a combination of normal and binomial distribution
#' \describe{
#' \item{type}{type of data}
#' \item{y}{result of the model y = -1 + mo2 + mo3 + ... + ad4 + ad5}
#' \item{mo2, mo3, mo4, mo5,
#' sc2, sc3, sc4, sc5,
#' ua2, ua3, ua4, ua5,
#' pd2, pd3, pd4, pd5,,
#' ad2, ad3, ad4, ad5,}{dummy variables for EQ5D data simulation}
#' \item{class}{original class of the data point}
#' \item{id}{id number of observations to simulated different persons}
#' \item{y_cens}{column y censored at 2 (upper boundary)}
#' ...
#' }
#' @source {simulated with true parameter values:
#' Class 1: sigma = XXX, theta = XXX and c(mo2,mo3,mo4,mo5, XXX) = c(XXX)
#' Class 2: sigma = XXX, theta = XXX and c(mo2,mo3,mo4,mo5, XXX) = c(XXX)}
#'
"simulated_data"
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