R/plot.episensr.booted.R

In dhaine/episensr: Basic Sensitivity Analysis of Epidemiological Results

#' Plot of bootstrap simulation output for selection and misclassification bias
#'
#' This takes an episensr bootstrap object and produces the plot of bootstrap replicates for selection or misclassification bias of the variable of interest, either relative risk or odds ratio. It also draws the confidence interval.
#'
#' @param x An object of class "episensr.booted" returned from the episensr bootstrap generation function.
#' @param association Choice between bias adjusted relative risk (rr) and odds ratio (or).
#' @param ... Other unused arguments.
#'
#' @seealso \code{\link{boot.bias}, \link{boot}, \link{selection}, \link{misclassification}}
#'
#' @examples
#' misclass_eval <- misclassification(matrix(c(215, 1449, 668, 4296),
#' dimnames = list(c("Breast cancer+", "Breast cancer-"),
#' c("Smoker+", "Smoker-")),
#' nrow = 2, byrow = TRUE),
#' type = "exposure",
#' bias_parms = c(.78, .78, .99, .99))
#'
#' set.seed(123)
#' misclass_boot <- boot.bias(misclass_eval)
#' plot(misclass_boot, association = "rr")
#'
#' @export
#' @importFrom ggplot2 ggplot geom_histogram aes after_stat geom_density geom_vline ggtitle xlab
plot.episensr.booted <- function(x,
                                 association = c("rr", "or"),
                                 ...) {
    association <- match.arg(association)
    .data <- as.data.frame(x[[2]]$t)
    colnames(.data) <- c("rr", "or")
    bins <- ceiling(length(.data$rr)/25)
    bins <- ifelse(bins < 10, 10,
            ifelse(bins > 100, 100, bins))

    if (association == "rr") {
        ggplot(.data, aes(x = .data$rr)) +
            geom_histogram(aes(y = after_stat(.data$density)), bins = bins,
                           colour = "grey", fill = "dimgrey") +
            geom_density() +
            geom_vline(xintercept = x$ci[1, 1], size = .75,
                       colour = "black", linetype = "dashed") +
            geom_vline(xintercept = x$ci[1, 2], size = .75,
                       colour = "black", linetype = "dashed") +
            ggtitle("Bias adjusted relative risk") +
            xlab("Relative risk")
    } else if (association == "or") {
        ggplot(.data, aes(x = .data$or)) +
            geom_histogram(aes(y = after_stat(.data$density)), bins = bins,
                           colour = "grey", fill = "dimgrey") +
            geom_density() +
            geom_vline(xintercept = x$ci[2, 1], size = .75,
                       colour = "black", linetype = "dashed") +
            geom_vline(xintercept = x$ci[2, 2], size = .75,
                       colour = "black", linetype = "dashed") +
            ggtitle("Bias adjusted odds ratio") +
            xlab("Odds ratio")
    }
}