\name{event.history}
\alias{event.history}
\title{Produces event.history graph for survival data}
\description{
  Produces an event history graph for right-censored survival data,
  including time-dependent covariate status, as described in
  Dubin, Muller, and Wang (2001).  Effectively,
  a Kaplan-Meier curve is produced with supplementary information
  regarding individual survival information, censoring information, and
  status over time of an individual time-dependent covariate or 
  time-dependent covariate function for both uncensored and censored 
  individuals.   
}
\usage{
event.history(data, survtime.col, surv.col,
              surv.ind = c(1, 0), subset.rows = NULL,
              covtime.cols = NULL, cov.cols = NULL,
              num.colors = 1, cut.cov = NULL, colors = 1,
              cens.density = 10, mult.end.cens = 1.05,
              cens.mark.right =FALSE, cens.mark = "-",
              cens.mark.ahead = 0.5, cens.mark.cutoff = -1e-08,
              cens.mark.cex = 1,
              x.lab = "time under observation",
              y.lab = "estimated survival probability",
              title = "event history graph", ...)
}
\arguments{
  \item{data}{
    A matrix or data frame with rows corresponding to units
    (often individuals) and columns corresponding to survival time,
    event/censoring indicator.  Also, multiple columns may be devoted to
    time-dependent covariate level and time change.
  }
  \item{survtime.col}{
    Column (in data) representing minimum of time-to-event or 
    right-censoring time for individual.
  }
  \item{surv.col}{
    Column (in data) representing event indicator for an individual.
    Though, traditionally, such an indicator will be 1 for an event and
    0 for a censored observation, this indicator can be represented 
    by any two numbers, made explicit by the surv.ind argument.
  }
  \item{surv.ind}{
    Two-element vector representing, respectively, the 
    number for an event, as listed in \code{surv.col}, 
    followed by the number for a censored
    observation.  Default is traditional survival data 
    represention, i.e., \code{c(1,0)}.
  }
  \item{subset.rows}{
    Subset of rows of original matrix or data frame (data) to 
    place in event history graph.
    Logical arguments may be used here (e.g., \code{treatment.arm == "a"}, if
    the data frame, data, has been attached to the search directory; 
  }
  \item{covtime.cols}{
    Column(s) (in data) representing the time when change of time-dependent 
    covariate (or time-dependent covariate function) occurs.  
    There should be a unique non-\code{NA} entry in the column for each such change 
    (along with corresponding \code{cov.cols} column entry representing 
    the value of the covariate or function at that change time).  
    Default is \code{NULL}, meaning no time-dependent covariate information 
    will be presented in the graph.  
  }
  \item{cov.cols}{
    Column(s) (in data) representing the level of the time-dependent 
    covariate (or time-dependent covariate function).  There should be 
    a unique non-\code{NA} column entry representing each change in the level 
    (along with a corresponding covtime.cols column entry representing 
    the time of the change).  Default is \code{NULL}, meaning
    no time-dependent covariate information will be presented in
    the graph. 
  }
  \item{num.colors}{
    Colors are utilized for the time-dependent covariate level for an
    individual.  This argument provides the number of unique covariate
    levels which will be displayed by mapping the number of colors 
    (via \code{num.colors}) to the number of desired covariate levels.  
    This will divide the covariate span into roughly equally-sized 
    intervals, via the S-Plus cut function.
    Default is one color, meaning no time-dependent information
    will be presented in the graph.  Note that this argument will
    be ignored/superceded if a non-NULL argument is provided for the
    \code{cut.cov} parameter.
  }
  \item{cut.cov}{
    This argument allows the user to explicitly state how to 
    define the intervals for the time-dependent covariate, such that
    different colors will be allocated to the user-defined covariate levels.
    For example, for plotting five colors, six ordered points within the 
    span of the data's covariate levels should be provided.
    Default is \code{NULL}, meaning that the \code{num.colors} argument value
    will dictate the number of breakpoints, with the covariate span
    defined into roughly equally-sized intervals via the S-Plus cut
    function.  However, if \code{is.null(cut.cov) == FALSE}, 
    then this argument supercedes any entry for the \code{num.colors} argument.
  }
  \item{colors}{
    This is a vector argument defining the actual colors used 
    for the time-dependent covariate levels in the plot, with the
    index of this vector corresponding to the ordered levels
    of the covariate.  The number of colors (i.e., the length
    of the colors vector) should correspond to the 
    value provided to the \code{num.colors} argument or the number 
    of ordered points - 1 as defined in the \code{cut.cov} argument
    (with \code{cut.cov} superceding \code{num.colors} if
    \code{is.null(cut.cov) == FALSE}).  
    The function, as currently written, allows for as much as 
    twenty distinct colors.  This argument effectively feeds
    into the col argument for the S-Plus polygon function.  
    Default is \code{colors = 1}.  See the col argument for the both the 
    S-Plus par function and polygon function for more information.
  }
  \item{cens.density}{
    This will provide the shading density at the end of the 
    individual bars for those who are censored.  For more information
    on shading density, see the density argument in the S-Plus
    polygon function.  Default is \code{cens.density=10}.
  }
  \item{mult.end.cens}{
    This is a multiplier that extends the length of 
    the longest surviving individual bar (or bars, if a tie exists) 
    if right-censored, presuming that no event times eventually follow this
    final censored time.  Default extends the length 5 percent beyond 
    the length of the observed right-censored survival time.
  }
  \item{cens.mark.right}{
    A logical argument that states whether an explicit mark 
    should be placed to the right of the individual right-censored 
    survival bars.  This argument is most useful for
    large sample sizes, where it may be hard to detect the special 
    shading via cens.density, particularly for the short-term survivors.
  }
  \item{cens.mark}{
    Character argument which describes the censored mark that should be
    used if \code{cens.mark.right = TRUE}.  Default is \code{"-"}.  
  }
  \item{cens.mark.ahead}{
    A numeric argument, which specifies the absolute distance
    to be placed between the individual right-censored
    survival bars and the mark as defined in the above cens.mark
    argument.  Default is 0.5 (that is, a half of day, if
    survival time is measured in days), but may very well need
    adjusting depending on the maximum survival time
    observed in the dataset.
  }
  \item{cens.mark.cutoff}{
    A negative number very close to 0 
    (by default \code{cens.mark.cutoff = -1e-8}) to ensure that 
    the censoring marks get plotted correctly.  See \code{event.history}
    code in order to see its usage.  This argument typically will not
    need adjustment.
  }
  \item{cens.mark.cex}{
    Numeric argument defining the size of the mark defined in 
    the \code{cens.mark} argument above.  See more information 
    by viewing the \code{cex} argument for the S-Plus \code{\link{par}} function.
    Default is \code{cens.mark.cex = 1.0}.
  }
  \item{x.lab}{Single label to be used for entire x-axis.  
    Default is \code{"time under observation"}. 
  }
  \item{y.lab}{Single label to be used for entire y-axis.  
    Default is \code{"estimated survival probability"}. 
  }
  \item{title}{Title for the event history graph.  
    Default is \code{"event history graph"}.
  }
  \item{\dots}{
    This allows arguments to the plot function call within 
    the \code{event.history} function.  
    So, for example, the axes representations can be manipulated
    with appropriate arguments, or particular areas of the \code{event.history} 
    graph can be \dQuote{zoomed}.  See the details section for more 
    comments about zooming.  
  }
}
\details{
  In order to focus on a particular area of the event history graph,
  zooming can be performed.  This is best done by 
  specifying appropriate \code{xlim} and \code{ylim} 
  arguments at the end of the \code{event.history} function call, 
  taking advantage of the \code{\dots} argument link to the plot function.
  An example of zooming can be seen
  in Plate 4 of the paper referenced below.
  
  Please read the reference below to understand how the
  individual covariate and survival information is provided in the plot,
  how ties are handled, how right-censoring is handled, etc.
}
\references{
  Dubin, J.A., Muller, H.-G., and Wang, J.-L. (2001).
  Event history graphs for censored survival data.
  \emph{Statistics in Medicine}, \bold{20}, 2951-2964.
}
\author{
  Joel Dubin\cr
  \email{jdubin@uwaterloo.ca}
}

\note{
  The authors have found better control of the use of color by 
  producing the graphs via the postscript plotting device
  in S-Plus.  In fact, the provided examples utilize 
  the postscript function.
  However, your past experiences may be different, 
  and you may prefer to control color directly (to the graphsheet
  in Windows environment, for example).  The event.history
  function will work with either approach.
}

\section{WARNING}{
  This function has been tested thoroughly, but only within 
  a restricted version and environment, 
  i.e., only within S-Plus 2000, Version 3, and within S-Plus 6.0,
  version 2, both on a Windows 2000 machine.  
  Hence, we cannot currently vouch
  for the function's effectiveness 
  in other versions of S-Plus (e.g., S-Plus 3.4) 
  nor in other operating environments (e.g., Windows 95, Linux or Unix).
  The function has also been verified to work on R under Linux.
}

\seealso{
  \code{\link{plot}},\code{\link{polygon}},
  \code{\link{event.chart}}, \code{\link{par}}
}

\examples{
# Code to produce event history graphs for SIM paper
#
# before generating plots, some pre-processing needs to be performed,
#  in order to get dataset in proper form for event.history function;
#  need to create one line per subject and sort by time under observation, 
#  with those experiencing event coming before those tied with censoring time;
require('survival')
data(heart)

# creation of event.history version of heart dataset (call heart.one):

heart.one <- matrix(nrow=length(unique(heart$id)), ncol=8)
for(i in 1:length(unique(heart$id)))
 {
  if(length(heart$id[heart$id==i]) == 1)
   heart.one[i,] <- as.numeric(unlist(heart[heart$id==i, ]))
  else if(length(heart$id[heart$id==i]) == 2)
   heart.one[i,] <- as.numeric(unlist(heart[heart$id==i,][2,]))
 }

heart.one[,3][heart.one[,3] == 0] <- 2 	## converting censored events to 2, from 0
if(is.factor(heart$transplant))
 heart.one[,7] <- heart.one[,7] - 1
 ## getting back to correct transplantation coding
heart.one <- as.data.frame(heart.one[order(unlist(heart.one[,2]), unlist(heart.one[,3])),])
names(heart.one) <- names(heart)
# back to usual censoring indicator:
heart.one[,3][heart.one[,3] == 2] <- 0 
# note: transplant says 0 (for no transplants) or 1 (for one transplant)
#        and event = 1 is death, while event = 0 is censored

# plot single Kaplan-Meier curve from heart data, first creating survival object
heart.surv <- survfit(Surv(stop, event) ~ 1, data=heart.one, conf.int = FALSE)

# figure 3: traditional Kaplan-Meier curve
# postscript('ehgfig3.ps', horiz=TRUE)
# omi <- par(omi=c(0,1.25,0.5,1.25))
 plot(heart.surv, ylab='estimated survival probability',
      xlab='observation time (in days)')
 title('Figure 3: Kaplan-Meier curve for Stanford data', cex=0.8)
# dev.off()

## now, draw event history graph for Stanford heart data; use as Figure 4

# postscript('ehgfig4.ps', horiz=TRUE, colors = seq(0, 1, len=20))
# par(omi=c(0,1.25,0.5,1.25))
 event.history(heart.one, 
		survtime.col=heart.one[,2], surv.col=heart.one[,3],
		covtime.cols = cbind(rep(0, dim(heart.one)[1]), heart.one[,1]),
		cov.cols = cbind(rep(0, dim(heart.one)[1]), heart.one[,7]),
		num.colors=2, colors=c(6,10),
		x.lab = 'time under observation (in days)',
		title='Figure 4: Event history graph for\nStanford data',
		cens.mark.right =TRUE, cens.mark = '-', 
		cens.mark.ahead = 30.0, cens.mark.cex = 0.85)
# dev.off()



# now, draw age-stratified event history graph for Stanford heart data; 
#  use as Figure 5

# two plots, stratified by age status
# postscript('c:\\temp\\ehgfig5.ps', horiz=TRUE, colors = seq(0, 1, len=20))
# par(omi=c(0,1.25,0.5,1.25))
 par(mfrow=c(1,2))

 event.history(data=heart.one, subset.rows = (heart.one[,4] < 0),
		survtime.col=heart.one[,2], surv.col=heart.one[,3],
		covtime.cols = cbind(rep(0, dim(heart.one)[1]), heart.one[,1]),
		cov.cols = cbind(rep(0, dim(heart.one)[1]), heart.one[,7]),
		num.colors=2, colors=c(6,10),  
		x.lab = 'time under observation\n(in days)',
		title = 'Figure 5a:\nStanford data\n(age < 48)',
		cens.mark.right =TRUE, cens.mark = '-', 
		cens.mark.ahead = 40.0, cens.mark.cex = 0.85,
		xlim=c(0,1900))

 event.history(data=heart.one, subset.rows = (heart.one[,4] >= 0),
		survtime.col=heart.one[,2], surv.col=heart.one[,3],
		covtime.cols = cbind(rep(0, dim(heart.one)[1]), heart.one[,1]),
		cov.cols = cbind(rep(0, dim(heart.one)[1]), heart.one[,7]),
		num.colors=2, colors=c(6,10),
		x.lab = 'time under observation\n(in days)',
		title = 'Figure 5b:\nStanford data\n(age >= 48)',
		cens.mark.right =TRUE, cens.mark = '-', 
		cens.mark.ahead = 40.0, cens.mark.cex = 0.85,
		xlim=c(0,1900))
# dev.off()
# par(omi=omi)

# we will not show liver cirrhosis data manipulation, as it was 
#  a bit detailed; however, here is the 
#  event.history code to produce Figure 7 / Plate 1

# Figure 7 / Plate 1 : prothrombin ehg with color
\dontrun{
second.arg <- 1				### second.arg is for shading
third.arg <- c(rep(1,18),0,1)		### third.arg is for intensity

# postscript('c:\\temp\\ehgfig7.ps', horiz=TRUE, 
# colors = cbind(seq(0, 1, len = 20), second.arg, third.arg)) 
# par(omi=c(0,1.25,0.5,1.25), col=19)
 event.history(cirrhos2.eh, subset.rows = NULL,
               survtime.col=cirrhos2.eh$time, surv.col=cirrhos2.eh$event,
		covtime.cols = as.matrix(cirrhos2.eh[, ((2:18)*2)]),
		cov.cols = as.matrix(cirrhos2.eh[, ((2:18)*2) + 1]),
		cut.cov =  as.numeric(quantile(as.matrix(cirrhos2.eh[, ((2:18)*2) + 1]),
				c(0,.2,.4,.6,.8,1), na.rm=TRUE) + c(-1,0,0,0,0,1)),	
 		colors=c(20,4,8,11,14),
		x.lab = 'time under observation (in days)',
		title='Figure 7: Event history graph for liver cirrhosis data (color)',
		cens.mark.right =TRUE, cens.mark = '-', 
		cens.mark.ahead = 100.0, cens.mark.cex = 0.85)
# dev.off()
}
}
\keyword{survival}