R/data.R

In PanelCount: Random Effects and/or Sample Selection Models for Panel Count Data

#' Simulated dataset with self-selection at both individual and individual-time level
#'
#' A simulated dataset with 200 individuals and 10 periods. The true data generating process is the following: \cr\cr
#' Selection equation (ProbitRE - Probit model with individual level random effects):
#' \deqn{z_{it}=1(1+x_{it}+w_{it}+u_i+\xi_{it} > 0}{z_it=1(1+x_it+w_it+u_i+\xi_it > 0)}
#' Outcome Equation (PLN_RE - Poisson Lognormal model with individual-time level random effects):
#' \deqn{E[y_{it}|x_{it},v_i,\epsilon_{it}] = exp(-1+x_{it} + v_i + \epsilon_{it})}{E[y_it|x_it,v_i,\epsilon_it] = exp(-1+x_it + v_i + \epsilon_it)}
#' Correlation (self-selection at both individual and individual-time level):
#' * \eqn{u_i} and \eqn{v_i} are bivariate normally distributed with a correlation of 0.25.
#' * \eqn{\xi_{it}}{\xi_it} and \eqn{\epsilon_{it}}{\epsilon_it} are bivariate normally distributed with a correlation of 0.5.
#' @md
#'
#' @format A simulated dataset with 200 individuals and 10 periods.
#' \describe{
#'   \item{id}{id, from 1-200}
#'   \item{time}{Time periods, from 1-10}
#'   \item{z}{Whether an individual is selected in a given period. Outcome is observed only when z=1}
#'   \item{y}{The outcome of an individual in a given period}
#'   \item{x}{A covariate influencing both z and y, with true effects being 1}
#'   \item{w}{A covariate influencing only z, with true effect being 1}
#' }
"sim"