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#' plotsesp()
#' plot the posterior densities for Se and Sp
#'
#' @param m The object generated by the metadiag function.
#' @param binwidth.p Histograms binwidth, default is 0.03.
#' @param CI.level Level of the posterior interval default is 0.95.
#' @seealso \code{\link{metadiag}}.
#' @keywords file
#' @examples
#'
#' ## execute analysis
#' \dontrun{
#' data(ep)
#' m1.ep <- metadiag(ep[,1:4])
#'
#' plotsesp(m = m1.ep)
#' }
#'
#' @import ggplot2
#' @import grid
#' @import gridExtra
#' @import R2jags
#' @import rjags
#' @importFrom stats median quantile
#'
#'@export
plotsesp <- function(m, binwidth.p = 0.03, CI.level = 0.95)
{
#if(class(m)!="rjags")stop("You have to provide a valid rjags object as fitted model")
# Patch for the "note" no-visible-binding-for-global-variable
se.pool <- m$BUGSoutput$sims.list$se.pool
sp.pool <- m$BUGSoutput$sims.list$sp.pool
se.new <- m$BUGSoutput$sims.list$se.new
sp.new <- m$BUGSoutput$sims.list$sp.new
lo <- (1 - CI.level)/2
up <- 1 - lo
p1 <- ggplot(data.frame(se.pool), aes_string(x = "se.pool")) +
geom_histogram(colour = "black", fill = "blue", binwidth = binwidth.p) +
xlim(0,1)+
xlab("Sensitivity (pooled)")+
geom_vline(xintercept = median(se.pool)) +
geom_vline(xintercept = quantile(se.pool, prob = c(lo, up)), linetype = "longdash")
p2 <- ggplot(data.frame(sp.pool), aes_string(x = "sp.pool")) +
geom_histogram(colour = "black", fill = "blue", binwidth = binwidth.p) +
xlim(0,1)+
xlab("Specificity (pooled)")+
geom_vline(xintercept = median(sp.pool)) +
geom_vline(xintercept = quantile(sp.pool, prob = c(lo, up)), linetype = "longdash")
p3 <- ggplot(data.frame(se.new), aes_string(x = "se.new")) +
geom_histogram(colour = "black", fill = "red", binwidth = binwidth.p) +
xlim(0,1)+
xlab("Sensitivity (predictive)")+
geom_vline(xintercept = median(se.new)) +
geom_vline(xintercept = quantile(se.new, prob = c(lo, up)), linetype = "longdash")
p4 <- ggplot(data.frame(sp.new), aes_string(x = "sp.new")) +
geom_histogram(colour = "black", fill = "red", binwidth = binwidth.p) +
xlim(0,1)+
xlab("Specificity (predictive)")+
geom_vline(xintercept = median(sp.new)) +
geom_vline(xintercept = quantile(sp.new, prob = c(lo, up)), linetype = "longdash")
grid.newpage()
pushViewport(viewport(layout = grid.layout(2, 2)))
vplayout <- function(x, y)
viewport(layout.pos.row = x,
layout.pos.col = y)
print(p1, vp = vplayout(1, 1))
print(p2, vp = vplayout(1, 2))
print(p3, vp = vplayout(2, 1))
print(p4, vp = vplayout(2, 2))
}
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