R/simoutput.R

In iriseekhout/Agree: Agreement and reliability between multiple raters

#' simoutput
#'
#' Output results for the simulation for different icc methods under various
#' conditions to investigate the sample size and number of raters requirements
#' for ICC and SEM calculations.
#'
#' @format A data frame with 2280 rows and 22 variables:
#' \describe{
#'   \item{n}{condition parameter: sample size}
#'   \item{cor}{condition parameter: raw correlation between raters}
#'   \item{k}{condition parameter: number of raters}
#'   \item{variance}{condition parameter: variance between patients}
#'   \item{deviation}{condition parameter: k raters with systematic deviation}
#'   \item{method}{condition parameter: icc method}
#'   \item{set}{condition parameter: simultion iteration (averaged)}
#'   \item{icc}{output parameter: average icc}
#'   \item{lower}{output parameter: average lower bound of CI for icc}
#'   \item{upper}{output parameter: average upper bound of CI for icc}
#'   \item{sem}{output parameter: average sem}
#'   \item{varpat}{output parameter: variance between patients}
#'   \item{varobs}{output parameter: variance between raters}
#'   \item{varerr}{output parameter: residual variance}
#'   \item{Ticc}{empirical population parameter: icc}
#'   \item{Tsem}{empirical population parameter: sem}
#'   \item{bias_icc}{result parameter: average bias for icc}
#'   \item{bias_sem}{result parameter: average bias for sem}
#'   \item{mse_icc}{result parameter: mean squared error for icc}
#'   \item{mse_sem}{result parameter: mean squared error for sem}
#'   \item{cov_icc}{result parameter: coverage of CI for icc}
#'   \item{width_icc}{result parameter: width of CI for icc}
#'   \item{width_sem}{result parameter: width of CI for sem}
#' }
#' @source data-raw/R/simoutput.R
"simoutput"