R/msmdata.R

In WeightIt: Weighting for Covariate Balance in Observational Studies

#' Simulated data for a 3 time point sequential study
#'
#' @description
#' This is a simulated dataset of 7500 units with covariates and treatment
#' measured three times and the outcome measured at the end from a hypothetical
#' observational study examining the effect of treatment delivered at each time
#' point on an adverse event.
#'
#'
#' @name msmdata
#' @docType data
#' @format A data frame with 7500 observations on the following 10 variables.
#' \describe{
#' \item{`X1_0`}{a count covariate measured at baseline}
#' \item{`X2_0`}{a binary covariate measured at baseline}
#' \item{`A_1`}{a binary indicator of treatment status at the first time point}
#' \item{`X1_1`}{a count covariate measured at the first time point (after the first treatment)}
#' \item{`X2_1`}{a binary covariate measured at the first time point (after the first treatment)}
#' \item{`A_2`}{a binary indicator of treatment status at the second time point}
#' \item{`X1_2`}{a count covariate measured at the second time point (after the second treatment)}
#' \item{`X2_2`}{a binary covariate measured at the first time point (after the first treatment)}
#' \item{`A_3`}{a binary indicator of treatment status at the third time point}
#' \item{`Y_B`}{a binary indicator of the outcome event (e.g., death)}
#' }
#' @keywords datasets
#' @examples
#'
#' data("msmdata")
#'
"msmdata"