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#' Plot method for a joint nested frailty model.
#'
#' Plots estimated baseline survival and hazard functions of a joint nested
#' frailty model (output from an object of class 'jointNestedPenal' for joint
#' nested frailty models) for each type of event (terminal or recurrent).
#' Confidence bands are allowed.
#'
#'
#' @aliases plot.jointNestedPenal lines.jointNestedPenal
#' @usage
#'
#' \method{plot}{jointNestedPenal}(x, event = "Both", type.plot = "Hazard",
#' conf.bands = FALSE, pos.legend="topright", cex.legend = 0.7, ylim, main,
#' color = 2, median=TRUE, Xlab = "Time", Ylab = "Hazard function", ...)
#' @param x A joint nested model, i.e. an object of class
#' \code{jointNestedPenal} for joint nested frailty model (output from calling
#' \code{frailtyPenal} function).
#' @param event a character string specifying the type of curve. Possible value
#' are "Terminal", "Recurrent", or "Both". The default is "Both".
#' @param type.plot a character string specifying the type of curve. Possible
#' value are "Hazard", or "Survival". The default is "Hazard". Only the first
#' letters are required, e.g "Haz", "Su"
#' @param conf.bands logical value. Determines whether confidence bands will be
#' plotted. The default is to do so.
#' @param pos.legend The location of the legend can be specified by setting
#' this argument to a single keyword from the list '"bottomright"', '"bottom"',
#' '"bottomleft"', '"left"', '"topleft"', '"top"', '"topright"', '"right"' and
#' '"center"'. The default is '"topright"'
#' @param cex.legend character expansion factor *relative* to current
#' 'par("cex")'. Default is 0.7
#' @param ylim y-axis limits
#' @param main plot title
#' @param color curve color (integer)
#' @param median Logical value. Determines whether survival median will be plotted. Default is TRUE.
#' @param Xlab Label of x-axis. Default is '"Time"'
#' @param Ylab Label of y-axis. Default is '"Hazard function"'
#' @param ... other unused arguments
#' @return Print a plot of the baseline survival or hazard functions for each
#' type of event or both with the confidence bands or not (conf.bands argument)
#' @seealso \code{\link{frailtyPenal}}
#' @keywords methods
##' @export
#' @examples
#'
#'
#' \dontrun{
#'
#' #-- here is generated cluster (30 clusters)
#' readmissionNested <- transform(readmission,group=id%%30+1)
#'
#' # Baseline hazard function approximated with splines with calendar-timescale
#'
#' model.spli.AG <- frailtyPenal(formula = Surv(t.start, t.stop, event)
#' ~ subcluster(id) + cluster(group) + dukes + terminal(death),
#' formula.terminalEvent = ~dukes, data = readmissionNested, recurrentAG = TRUE,
#' n.knots = 8, kappa = c(9.55e+9, 1.41e+12),initialize = TRUE)
#'
#' # Plot the estimated baseline hazard function with the confidence intervals
#' plot(model.spli.AG)
#'
#' # Plot the estimated baseline hazard function with the confidence intervals
#' plot(model.spli.RE, type = "Survival")
#'
#' }
#'
"plot.jointNestedPenal" <-
function (x, event="Both", type.plot="Hazard", conf.bands=FALSE, pos.legend="topright", cex.legend=0.7, ylim, main, color=2, median=TRUE, Xlab = "Time", Ylab = "Hazard function", ...){
event.type <- charmatch(event, c("Both", "Recurrent", "Terminal"), nomatch = 0)
if (event.type == 0) {
stop("event must be 'Both', 'Recurrent' or 'Terminal'")
}
plot.type <- charmatch(type.plot, c("Hazard", "Survival"), nomatch = 0)
if (plot.type == 0) {
stop("estimator must be 'Hazard' or 'Survival'")
}
if(missing(main)) main<-""
if (event.type==1){ # both
if(plot.type==1){
if (missing(ylim)){
yymax<-max(c(x$lamR, x$lamD),na.rm=TRUE)
yymin<-min(c(x$lamR, x$lamD),na.rm=TRUE)
}else{
yymax<-ylim[2]
yymin<-ylim[1]
}
if (conf.bands){
matplot(x$xR[,1], x$lamR[,,1], col=color, type="l", lty=c(1,2,2), xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
for (i in (1:x$n.strat)[-1]) matlines(x$xR[,i], x$lamR[,,i], col=color+(i-1), type="l", lty=c(1,2,2), ...)
matlines(x$xD, x$lamD, col=color+x$n.strat, type="l", lty=c(1,2,2), ...)
}else{
plot(x$xR[,1], x$lamR[,1,1], col=color, type="l", lty=1, xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
for (i in (1:x$n.strat)[-1]) lines(x$xR[,i], x$lamR[,1,i], col=color+(i-1), type="l", lty=1, ...)
lines(x$xD, x$lamD[,1], col=color+x$n.strat, type="l", lty=1, ...)
}
}else{
if (missing(Ylab)) Ylab <- "Baseline survival function"
if (missing(ylim)){
yymax<-1
yymin<-0
}else{
yymax<-ylim[2]
yymin<-ylim[1]
}
if (x$typeof == 0){
if (conf.bands){
matplot(x$xR[,1], x$survR[,,1], col=color, type="l", lty=c(1,2,2), xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
for (i in (1:x$n.strat)[-1]) matlines(x$xR[,i], x$survR[,,i], col=color+(i-1), type="l", lty=c(1,2,2), ...)
matlines(x$xD, x$survD, col=color+x$n.strat, type="l", lty=c(1,2,2), ...)
if (median){abline(a=0.5,b=0,cex=.5,col=1,lty=3)}
}else{
plot(x$xR[,1], x$survR[,1,1], col=color, type="l", lty=1, xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
for (i in (1:x$n.strat)[-1]) lines(x$xR[,i], x$survR[,1,i], col=color+(i-1), type="l", lty=1, ...)
lines(x$xD, x$survD[,1], col=color+x$n.strat, type="l", lty=1, ...)
if (median){abline(a=0.5,b=0,cex=.5,col=1,lty=3)}
}
}else{
if (conf.bands){
matplot(x$xSuR[,1], x$survR[,,1], col=color, type="l", lty=c(1,2,2), xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
for (i in (1:x$n.strat)[-1]) matlines(x$xSuR[,i], x$survR[,,i], col=color+(i-1), type="l", lty=c(1,2,2), ...)
matlines(x$xSuD, x$survD, col=color+x$n.strat, type="l", lty=c(1,2,2), ...)
if (median){abline(a=0.5,b=0,cex=.5,col=1,lty=3)}
}
else{
plot(x$xSuR[,1], x$survR[,1,1], col=color, type="l", lty=1, xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
for (i in (1:x$n.strat)[-1]) lines(x$xSuR[,i], x$survR[,1,i], col=color+(i-1), type="l", lty=1, ...)
lines(x$xSuD, x$survD[,1], col=color+x$n.strat, type="l", lty=1, ...)
if (median){abline(a=0.5,b=0,cex=.5,col=1,lty=3)}
}
}
}
legend(pos.legend, c("recurrent event","terminal event"), lty=1, col=c(color,color+x$n.strat), xjust=1, cex=cex.legend, ...)
}
if (event.type==2){ # recurrent
if(plot.type==1){
if (missing(ylim)){
yymax<-max(x$lamR,na.rm=TRUE)
yymin<-min(x$lamR,na.rm=TRUE)
}else{
yymax<-ylim[2]
yymin<-ylim[1]
}
if (conf.bands){
matplot(x$xR[,1], x$lamR[,,1], col=color, type="l", lty=c(1,2,2), xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
for (i in (1:x$n.strat)[-1]) matlines(x$xR[,i], x$lamR[,,i], col=color+(i-1), type="l", lty=c(1,2,2), ...)
}else{
plot(x$xR[,1], x$lamR[,1,1], col=color, type="l", lty=1, xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
for (i in (1:x$n.strat)[-1]) lines(x$xR[,i], x$lamR[,1,i], col=color+(i-1), type="l", lty=1, ...)
}
}else{
if (missing(Ylab)) Ylab <- "Baseline survival function"
if (missing(ylim)){
yymax<-1
yymin<-0
}else{
yymax<-ylim[2]
yymin<-ylim[1]
}
if (x$typeof == 0){
if (conf.bands){
matplot(x$xR[,1], x$survR[,,1], col=color, type="l", lty=c(1,2,2), xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
for (i in (1:x$n.strat)[-1]) matlines(x$xR[,i], x$survR[,,i], col=color+(i-1), type="l", lty=c(1,2,2), ...)
if (median){abline(a=0.5,b=0,cex=.5,col=1,lty=3)}
}else{
plot(x$xR[,1], x$survR[,1,1], col=color, type="l", lty=1, xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
for (i in (1:x$n.strat)[-1]) lines(x$xR[,i], x$survR[,1,i], col=color+(i-1), type="l", lty=1, ...)
if (median){abline(a=0.5,b=0,cex=.5,col=1,lty=3)}
}
}else{
if (conf.bands){
matplot(x$xSuR[,1], x$survR[,,1], col=color, type="l", lty=c(1,2,2), xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
for (i in (1:x$n.strat)[-1]) matlines(x$xSuR[,i], x$survR[,,i], col=color+(i-1), type="l", lty=c(1,2,2), ...)
if (median){abline(a=0.5,b=0,cex=.5,col=1,lty=3)}
}else{
plot(x$xSuR[,1], x$survR[,1,1], col=color, type="l", lty=1, xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
for (i in (1:x$n.strat)[-1]) lines(x$xSuR[,i], x$survR[,1,i], col=color+(i-1), type="l", lty=1, ...)
if (median){abline(a=0.5,b=0,cex=.5,col=1,lty=3)}
}
}
}
legend(pos.legend, c("recurrent event"), lty=1, col=color, xjust=1, cex=cex.legend, ...)
}
if (event.type==3){ # terminal
if(plot.type==1){
if (missing(ylim)){
yymax<-max(x$lamD,na.rm=TRUE)
yymin<-min(x$lamD,na.rm=TRUE)
}else{
yymax<-ylim[2]
yymin<-ylim[1]
}
if (conf.bands){
matplot(x$xD, x$lamD, col=color+x$n.strat, type="l", lty=c(1,2,2), xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
}else{
plot(x$xD, x$lamD[,1], col=color+x$n.strat, type="l", lty=1, xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
}
}else{
if (missing(ylim)){
yymax<-1
yymin<-0
}else{
yymax<-ylim[2]
yymin<-ylim[1]
}
if (x$typeof == 0){
if (conf.bands){
matplot(x$xD, x$survD, col=color+x$n.strat, type="l", lty=c(1,2,2), xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
if (median){abline(a=0.5,b=0,cex=.5,col=1,lty=3)}
}else{
plot(x$xD, x$survD[,1], col=color+x$n.strat, type="l", lty=1, xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
if (median){abline(a=0.5,b=0,cex=.5,col=1,lty=3)}
}
}else{
if (conf.bands){
matplot(x$xSuD, x$survD, col=color+x$n.strat, type="l", lty=c(1,2,2), xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
if (median){abline(a=0.5,b=0,cex=.5,col=1,lty=3)}
}else{
plot(x$xSuD, x$survD[,1], col=color+x$n.strat, type="l", lty=1, xlab=Xlab,ylab=Ylab, ylim=c(yymin,yymax), main=main, ...)
if (median){abline(a=0.5,b=0,cex=.5,col=1,lty=3)}
}
}
}
legend(pos.legend, c("terminal event"), lty=1, col=color+x$n.strat, xjust=1, cex=cex.legend, ...)
}
return(invisible())
}
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