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#' Graph fitted stratified survival curves from Cox Proportional Hazards models
#'
#' \code{ggfitStrata} graphs fitted survival curves created with
#' \code{\link{survfit}} using ggplot2.
#'
#' @param obj a \code{survfit} object.
#' @param byStrata logical, whether or not you want to include all of the
#' stratified survival curves on one plot or separate them into a grid arranged
#' plot.
#' @param xlab a label for the plot's x-axis
#' @param ylab a label of the plot's y-axis
#' @param title plot title.
#' @param lcolour line color. Currently only works if \code{byStrata = TRUE}.
#' The default it \code{lcolour = "#2C7FB8"} (a bluish hexadecimal colour)
#' @param rcolour confidence bounds ribbon color. Either a single color or a
#' vector of colours. The default it \code{lcolour = "#2C7FB8"}
#' (a bluish hexadecimal colour)
#'
#' @description This function largely improves \code{\link{plot.survfit}}. It
#' plots the curves using ggplot2 rather than base R graphics. One major
#' advantage is the ability to split the survival curves into multiple plots and
#' arrange them in a grid. This makes it easier to examine many strata at once.
#' Otherwise they can be very bunched up.
#'
#' Note: the strata legend labels need to be changed manually (see
#' \code{revalue}) in the \code{survfit} object with the \code{strata}
#' component.
#'
#' @examples
#' # Load packages
#' library(survival)
#' library(simPH)
#'
#' # Subset data
#' bladder1 <- bladder[bladder$enum < 5, ]
#'
#' # Estimate coxph model (note that this model is for code illustration only)
#' M1 <- coxph(Surv(stop, event) ~ (rx + size + number) + strata(enum) +
#' cluster(id), bladder1)
#'
#' # Find predicted values
#' M1Fit <- survfit(M1)
#'
#' # Plot strata in a grid
#' ggfitStrata(M1Fit, byStrata = TRUE)
#'
#' # Plot all in one
#' ggfitStrata(M1Fit, byStrata = FALSE)
#'
#' @seealso \code{\link{survfit}}, \code{ggplot2} and
#' \code{\link{strata}}
#' @import ggplot2
#' @importFrom gridExtra grid.arrange
#' @export
ggfitStrata <- function(obj, byStrata = FALSE, xlab = "", ylab = "", title = "",
lcolour = "#2C7FB8", rcolour = "#2C7FB8")
{
Strata <- Lower <- Upper <- StrataC <- Time <- Survival <- NULL
sFit <- obj
time <- sFit$time
lower <- sFit$lower
upper <- sFit$upper
S <- sFit$surv
strata <- sFit$strata
strata <- factor(rep(names(strata), strata), levels = names(strata))
TempData <- data.frame(Time = time, Lower = lower,
Upper = upper, Survival = S,
Strata = strata)
if (byStrata == FALSE){
ggplot(data = TempData, aes(x = Time,
y = Survival,
color = Strata,
fill = Strata)) +
geom_line() +
geom_ribbon(aes(ymin = Lower, ymax = Upper), alpha = I(0.1)) +
xlab(xlab) + ylab(ylab) + ggtitle(title) +
theme_bw()
} else if (byStrata == TRUE){
TempData$StrataC <- gsub("=", "", TempData$Strata)
TempData$StrataC <- gsub(" ", "", TempData$StrataC)
eachStrata <- unique(TempData$StrataC)
p <- list()
for (i in eachStrata){
SubData <- subset(TempData, StrataC == i)
p[[i]] <- ggplot(data = SubData, aes(x = Time,
y = Survival)) +
geom_line(colour = lcolour) +
geom_ribbon(aes(ymin = Lower,
ymax = Upper),
alpha = I(0.1),
colour = NA,
fill = rcolour) +
xlab("") + ylab("") +
ggtitle(paste(i, "\n")) +
theme_bw()
}
Grid <- do.call(grid.arrange, c(p, top = title, bottom = xlab,
left = ylab))
}
}
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