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#' Artifical data set used to test the functionality of confoundr.
#'
#' The toy_long data set contains 30,000 records and 15
#' variables. These variables include time-varying exposures,
#' outcomes, and covariates, along with strata and censoring
#' indicators. Time-varying inverse-probability-of-exposure
#' weights and censoring weights are available as well.
#'
#' @docType data
#' @usage data(toy_long)
#'
#' @format A data frame with 3,000 rows and 13 variables:
#' \describe{
#' \item{uid}{subject ID}
#' \item{time}{time of observation}
#' \item{a}{exposure measurement at time t}
#' \item{l}{covariate measurement at time t}
#' \item{m}{covariate measurement at time t}
#' \item{n}{covariate measurement at time t}
#' \item{o}{covariate measurement at time t}
#' \item{p}{covariate measurement at time t}
#' \item{s}{censoring indicator at time t}
#' \item{h}{exposure history at time t}
#' \item{hx}{grouped exposure history, by p_0, at time t}
#' \item{wa}{inverse probability of exposure and censoring weight at time t}
#' \item{wax}{cumulative inverse probability of exposure weight at time t}
#' \item{wsx}{cumulative inverse probability of censoring weight at time t}
#' \item{e5}{propensity score strata at time t}
#'
#' }
#'
"toy_long"
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