superb: Summary Plots with Adjusted Error Bars

#' Data for Figure 4
#'
#' The data, inspired from \insertCite{c17}{superb}, shows an example where the
#' "stand-alone" 95\% confidence interval of the means returns
#' a result in contradiction with the result of a statistical test.
#' The paradoxical result is resolved by using adjusted confidence intervals,
#' here the population size-adjusted confidence interval.
#'
#' @docType data
#'
#' @md
#'
#' @usage data(dataFigure4)
#'
#' @format An object of class data.frame.
#'
#' @keywords datasets
#'
#' @references 
#' \insertAllCited{}
#'
#' @source \doi{10.5709/acp-0214-z}
#'
#' @examples
#' library(ggplot2)
#' library(gridExtra)
#' data(dataFigure4)
#' 
#' options(superb.feedback = 'none') # shut down 'warnings' and 'design' interpretation messages
#' 
#' ## realize the plot with unadjusted (left) and ajusted (right) 95% confidence intervals
#' plt4a = superb(
#'     score ~ group,
#'     dataFigure4, 
#'     adjustments=list(purpose = "single", popSize = Inf), 
#'     plotStyle="bar" ) + 
#'   xlab("Group") + ylab("Score") + labs(title="Difference-adjusted 95% CI\n") +
#'   coord_cartesian( ylim = c(85,115) ) +
#'   geom_hline(yintercept = 100, colour = "black", linewidth = 0.5, linetype=2)
#' plt4b = superb(
#'     score ~ group,
#'     dataFigure4, 
#'     adjustments=list(purpose = "single", popSize = 50 ), 
#'     plotStyle="bar" ) + 
#'   xlab("Group") + ylab("Score") + labs(title="Population size and difference-\nadjusted 95% CI") +
#'   coord_cartesian( ylim = c(85,115) ) + 
#'   geom_hline(yintercept = 100, colour = "black", linewidth = 0.5, linetype=2)
#' plt4 = grid.arrange(plt4a,plt4b,ncol=2)
#' 
#' ## realise the correct t-test to see the discrepancy
#' res = t.test(dataFigure4$score, mu=100)
#' tcorr = res$statistic /sqrt(1-25/50)
#' pcorr = 1-pt(tcorr,24)
#' c(tcorr, pcorr)
#' 
#' 
"dataFigure4"