Flexible Event Chart for Time-to-Event Data
Creates an event chart on the current graphics device. Also, allows user to plot legend on plot area or on separate page. Contains features useful for plotting data with time-to-event outcomes Which arise in a variety of studies including randomized clinical trials and non-randomized cohort studies. This function can use as input a matrix or a data frame, although greater utility and ease of use will be seen with a data frame.
event.chart(data, subset.r = 1:dim(data)[1], subset.c = 1:dim(data)[2], sort.by = NA, sort.ascending = TRUE, sort.na.last = TRUE, sort.after.subset = TRUE, y.var = NA, y.var.type = "n", y.jitter = FALSE, y.jitter.factor = 1, y.renum = FALSE, NA.rm = FALSE, x.reference = NA, now = max(data[, subset.c], na.rm = TRUE), now.line = FALSE, now.line.lty = 2, now.line.lwd = 1, now.line.col = 1, pty = "m", date.orig = c(1, 1, 1960), titl = "Event Chart", y.idlabels = NA, y.axis = "auto", y.axis.custom.at = NA, y.axis.custom.labels = NA, y.julian = FALSE, y.lim.extend = c(0, 0), y.lab = ifelse(is.na(y.idlabels), "", as.character(y.idlabels)), x.axis.all = TRUE, x.axis = "auto", x.axis.custom.at = NA, x.axis.custom.labels = NA, x.julian = FALSE, x.lim.extend = c(0, 0), x.scale = 1, x.lab = ifelse(x.julian, "Follow-up Time", "Study Date"), line.by = NA, line.lty = 1, line.lwd = 1, line.col = 1, line.add = NA, line.add.lty = NA, line.add.lwd = NA, line.add.col = NA, point.pch = 1:length(subset.c), point.cex = rep(0.6, length(subset.c)), point.col = rep(1, length(subset.c)), point.cex.mult = 1., point.cex.mult.var = NA, extra.points.no.mult = rep(NA, length(subset.c)), legend.plot = FALSE, legend.location = "o", legend.titl = titl, legend.titl.cex = 3, legend.titl.line = 1, legend.point.at = list(x = c(5, 95), y = c(95, 30)), legend.point.pch = point.pch, legend.point.text = ifelse(rep(is.data.frame(data), length(subset.c)), names(data[, subset.c]), subset.c), legend.cex = 2.5, legend.bty = "n", legend.line.at = list(x = c(5, 95), y = c(20, 5)), legend.line.text = names(table(as.character(data[, line.by]), exclude = c("", "NA"))), legend.line.lwd = line.lwd, legend.loc.num = 1, ...)
data |
a matrix or data frame with rows corresponding to subjects and columns corresponding to variables. Note that for a data frame or matrix containing multiple time-to-event data (e.g., time to recurrence, time to death, and time to last follow-up), one column is required for each specific event. |
subset.r |
subset of rows of original matrix or data frame to place in event chart.
Logical arguments may be used here (e.g., |
subset.c |
subset of columns of original matrix or data frame to place in event chart;
if working with a data frame, a vector of data frame variable names may be
used for subsetting purposes (e.g., |
sort.by |
column(s) or data frame variable name(s) with which to sort the chart's output.
The default is |
sort.ascending |
logical flag (which takes effect only if the argument |
sort.na.last |
logical flag (which takes effect only if the argument |
sort.after.subset |
logical flag (which takes effect only if the argument sort.by is utilized).
If |
y.var |
variable name or column number of original matrix or data frame with
which to scale y-axis.
Default is |
y.var.type |
type of variable specified in |
y.jitter |
logical flag (which takes effect only if the argument
The default of |
y.jitter.factor |
an argument used with the |
y.renum |
logical flag. If |
NA.rm |
logical flag. If |
x.reference |
column of original matrix or data frame with which to reference the x-axis.
That is, if specified, all columns specified in |
now |
the “now” date which will be used for top of y-axis
when creating the Goldman eventchart (see reference below).
Default is |
now.line |
logical flag. A feature utilized by the Goldman Eventchart.
When |
now.line.lty |
line type of |
now.line.lwd |
line width of |
now.line.col |
color of |
pty |
graph option, |
date.orig |
date of origin to consider if dates are in julian, SAS , or S-Plus dates
object format; default is January 1, 1960 (which is the default origin
used by both S-Plus and SAS). Utilized when either
|
titl |
title for event chart. Default is 'Event Chart'. |
y.idlabels |
column or data frame variable name used for y-axis labels. For example,
if |
y.axis |
character string specifying whether program will control labelling
of y-axis (with argument |
y.axis.custom.at |
user-specified vector of y-axis label locations.
Must be used when |
y.axis.custom.labels |
user-specified vector of y-axis labels.
Must be used when |
y.julian |
logical flag (which will only be considered if |
y.lim.extend |
two-dimensional vector representing the number of units that the user
wants to increase |
y.lab |
single label to be used for entire y-axis. Default will be the variable name
or column number of |
x.axis.all |
logical flag. If |
x.axis |
character string specifying whether program will control labelling
of x-axis (with argument |
x.axis.custom.at |
user-specified vector of x-axis label locations.
Must be used when |
x.axis.custom.labels |
user-specified vector of x-axis labels.
Must be used when |
x.julian |
logical flag (which will only be considered if |
x.lim.extend |
two-dimensional vector representing the number of time units (usually in days)
that the user wants to increase |
x.scale |
a factor whose reciprocal is multiplied to original units of the
x-axis. For example, if the original data frame is in units of days,
|
x.lab |
single label to be used for entire x-axis. Default will be “On Study Date”
if |
line.by |
column or data frame variable name for plotting unique lines by unique
values of vector (e.g., specify |
line.lty |
vector of line types corresponding to ascending order of |
line.lwd |
vector of line widths corresponding to ascending order of |
line.col |
vector of line colors corresponding to ascending order of |
line.add |
a 2xk matrix with k=number of pairs of additional line segments to add.
For example, if it is of interest to draw additional line segments
connecting events one and two, two and three, and four and five,
(possibly with different colors), an appropriate The convention use of If NOTE: The drawing of the original default line
may be suppressed (with |
line.add.lty |
a kx1 vector corresponding to the columns of |
line.add.lwd |
a kx1 vector corresponding to the columns of |
line.add.col |
a kx1 vector corresponding to the columns of |
point.pch |
vector of |
point.cex |
vector of size of points representing each event.
If |
point.col |
vector of colors of points representing each event.
If |
point.cex.mult |
a single number (may be non-integer), which is the base multiplier for the value of
the |
point.cex.mult.var |
vector of variables to be used in determining what point.cex.mult is multiplied by
for determining size of plotted points from (possibly a subset of)
|
extra.points.no.mult |
vector of variables in the dataset to ignore for purposes of using
|
legend.plot |
logical flag; if |
legend.location |
will be used only if |
legend.titl |
title for the legend; default is title to be used for main plot.
Only used when |
legend.titl.cex |
size of text for legend title. Only used when |
legend.titl.line |
line location of legend title dictated by |
legend.point.at |
location of upper left and lower right corners of legend area to be utilized for describing events via points and text. |
legend.point.pch |
vector of |
legend.point.text |
text to be used for describing events; the default is setup for a data frame,
as it will print the names of the columns specified by |
legend.cex |
size of text for points and event descriptions. Default is 2.5 which is setup
for |
legend.bty |
option to put a box around the legend(s); default is to have no box
( |
legend.line.at |
if |
legend.line.text |
text to be used for describing |
legend.line.lwd |
vector of line widths corresponding to |
legend.loc.num |
number used for locator argument when |
... |
additional par arguments for use in main plot. |
if you want to put, say, two eventcharts side-by-side, in a plot
region, you should not set up par(mfrow=c(1,2))
before running the
first plot. Instead, you should add the argument mfg=c(1,1,1,2)
to the first plot call followed by the argument mfg=c(1,2,1,2)
to the second plot call.
if dates in original data frame are in a specialized form
(eg., mm/dd/yy) of mode CHARACTER, the user must convert those columns to
become class dates or julian numeric mode (see Date
for more information).
For example, in a data frame called testdata
, with specialized
dates in columns 4 thru 10, the following code could be used:
as.numeric(dates(testdata[,4:10]))
. This will convert the columns
to numeric julian dates based on the function's default origin
of January 1, 1960. If original dates are in class dates or julian form,
no extra work is necessary.
In the survival analysis, the data typically come in two
columns: one column containing survival time and the other
containing censoring indicator or event code. The
event.convert
function converts this type of data into
multiple columns of event times, one column of each event
type, suitable for the event.chart
function.
an event chart is created on the current graphics device. If legend.plot =TRUE and legend.location = 'o', a one-page legend will precede the event chart. Please note that par parameters on completion of function will be reset to par parameters existing prior to start of function.
J. Jack Lee and Kenneth R. Hess
Department of Biostatistics
University of Texas
M.D. Anderson Cancer Center
Houston, TX 77030
jjlee@mdanderson.org, khess@mdanderson.org
Joel A. Dubin
Department of Statistics
University of Waterloo
jdubin@uwaterloo.ca
Lee J.J., Hess, K.R., Dubin, J.A. (2000). Extensions and applications of event charts. The American Statistician, 54:1, 63–70.
Dubin, J.A., Lee, J.J., Hess, K.R. (1997). The Utility of Event Charts. Proceedings of the Biometrics Section, American Statistical Association.
Dubin, J.A., Muller H-G, Wang J-L (2001). Event history graphs for censored survival data. Statistics in Medicine, 20: 2951–2964.
Goldman, A.I. (1992). EVENTCHARTS: Visualizing Survival and Other Timed-Events Data. The American Statistician, 46:1, 13–18.
# The sample data set is an augmented CDC AIDS dataset (ASCII) # which is used in the examples in the help file. This dataset is # described in Kalbfleisch and Lawless (JASA, 1989). # Here, we have included only children 4 years old and younger. # We have also added a new field, dethdate, which # represents a fictitious death date for each patient. There was # no recording of death date on the original dataset. In addition, we have # added a fictitious viral load reading (copies/ml) for each patient at time of AIDS diagnosis, # noting viral load was also not part of the original dataset. # # All dates are julian with julian=0 being # January 1, 1960, and julian=14000 being 14000 days beyond # January 1, 1960 (i.e., May 1, 1998). cdcaids <- data.frame( age=c(4,2,1,1,2,2,2,4,2,1,1,3,2,1,3,2,1,2,4,2,2,1,4,2,4,1,4,2,1,1,3,3,1,3), infedate=c( 7274,7727,7949,8037,7765,8096,8186,7520,8522,8609,8524,8213,8455,8739, 8034,8646,8886,8549,8068,8682,8612,9007,8461,8888,8096,9192,9107,9001, 9344,9155,8800,8519,9282,8673), diagdate=c( 8100,8158,8251,8343,8463,8489,8554,8644,8713,8733,8854,8855,8863,8983, 9035,9037,9132,9164,9186,9221,9224,9252,9274,9404,9405,9433,9434,9470, 9470,9472,9489,9500,9585,9649), diffdate=c( 826,431,302,306,698,393,368,1124,191,124,330,642,408,244,1001,391,246, 615,1118,539,612,245,813,516,1309,241,327,469,126,317,689,981,303,976), dethdate=c( 8434,8304,NA,8414,8715,NA,8667,9142,8731,8750,8963,9120,9005,9028,9445, 9180,9189,9406,9711,9453,9465,9289,9640,9608,10010,9488,9523,9633,9667, 9547,9755,NA,9686,10084), censdate=c( NA,NA,8321,NA,NA,8519,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA, NA,NA,NA,NA,NA,NA,NA,NA,NA,10095,NA,NA), viralload=c( 13000,36000,70000,90000,21000,110000,75000,12000,125000,110000,13000,39000,79000,135000,14000, 42000,123000,20000,12000,18000,16000,140000,16000,58000,11000,120000,85000,31000,24000,115000, 17000,13100,72000,13500) ) cdcaids <- upData(cdcaids, labels=c(age ='Age, y', infedate='Date of blood transfusion', diagdate='Date of AIDS diagnosis', diffdate='Incubation period (days from HIV to AIDS)', dethdate='Fictitious date of death', censdate='Fictitious censoring date', viralload='Fictitious viral load')) # Note that the style options listed with these # examples are best suited for output to a postscript file (i.e., using # the postscript function with horizontal=TRUE) as opposed to a graphical # window (e.g., motif). # To produce simple calendar event chart (with internal legend): # postscript('example1.ps', horizontal=TRUE) event.chart(cdcaids, subset.c=c('infedate','diagdate','dethdate','censdate'), x.lab = 'observation dates', y.lab='patients (sorted by AIDS diagnosis date)', titl='AIDS data calendar event chart 1', point.pch=c(1,2,15,0), point.cex=c(1,1,0.8,0.8), legend.plot=TRUE, legend.location='i', legend.cex=1.0, legend.point.text=c('transfusion','AIDS diagnosis','death','censored'), legend.point.at = list(c(7210, 8100), c(35, 27)), legend.bty='o') # To produce simple interval event chart (with internal legend): # postscript('example2.ps', horizontal=TRUE) event.chart(cdcaids, subset.c=c('infedate','diagdate','dethdate','censdate'), x.lab = 'time since transfusion (in days)', y.lab='patients (sorted by AIDS diagnosis date)', titl='AIDS data interval event chart 1', point.pch=c(1,2,15,0), point.cex=c(1,1,0.8,0.8), legend.plot=TRUE, legend.location='i', legend.cex=1.0, legend.point.text=c('transfusion','AIDS diagnosis','death','censored'), x.reference='infedate', x.julian=TRUE, legend.bty='o', legend.point.at = list(c(1400, 1950), c(7, -1))) # To produce simple interval event chart (with internal legend), # but now with flexible diagdate symbol size based on viral load variable: # postscript('example2a.ps', horizontal=TRUE) event.chart(cdcaids, subset.c=c('infedate','diagdate','dethdate','censdate'), x.lab = 'time since transfusion (in days)', y.lab='patients (sorted by AIDS diagnosis date)', titl='AIDS data interval event chart 1a, with viral load at diagdate represented', point.pch=c(1,2,15,0), point.cex=c(1,1,0.8,0.8), point.cex.mult = 0.00002, point.cex.mult.var = 'viralload', extra.points.no.mult = c(1,NA,1,1), legend.plot=TRUE, legend.location='i', legend.cex=1.0, legend.point.text=c('transfusion','AIDS diagnosis','death','censored'), x.reference='infedate', x.julian=TRUE, legend.bty='o', legend.point.at = list(c(1400, 1950), c(7, -1))) # To produce more complicated interval chart which is # referenced by infection date, and sorted by age and incubation period: # postscript('example3.ps', horizontal=TRUE) event.chart(cdcaids, subset.c=c('infedate','diagdate','dethdate','censdate'), x.lab = 'time since diagnosis of AIDS (in days)', y.lab='patients (sorted by age and incubation length)', titl='AIDS data interval event chart 2 (sorted by age, incubation)', point.pch=c(1,2,15,0), point.cex=c(1,1,0.8,0.8), legend.plot=TRUE, legend.location='i',legend.cex=1.0, legend.point.text=c('transfusion','AIDS diagnosis','death','censored'), x.reference='diagdate', x.julian=TRUE, sort.by=c('age','diffdate'), line.by='age', line.lty=c(1,3,2,4), line.lwd=rep(1,4), line.col=rep(1,4), legend.bty='o', legend.point.at = list(c(-1350, -800), c(7, -1)), legend.line.at = list(c(-1350, -800), c(16, 8)), legend.line.text=c('age = 1', ' = 2', ' = 3', ' = 4')) # To produce the Goldman chart: # postscript('example4.ps', horizontal=TRUE) event.chart(cdcaids, subset.c=c('infedate','diagdate','dethdate','censdate'), x.lab = 'time since transfusion (in days)', y.lab='dates of observation', titl='AIDS data Goldman event chart 1', y.var = c('infedate'), y.var.type='d', now.line=TRUE, y.jitter=FALSE, point.pch=c(1,2,15,0), point.cex=c(1,1,0.8,0.8), mgp = c(3.1,1.6,0), legend.plot=TRUE, legend.location='i',legend.cex=1.0, legend.point.text=c('transfusion','AIDS diagnosis','death','censored'), x.reference='infedate', x.julian=TRUE, legend.bty='o', legend.point.at = list(c(1500, 2800), c(9300, 10000))) # To convert coded time-to-event data, then, draw an event chart: surv.time <- c(5,6,3,1,2) cens.ind <- c(1,0,1,1,0) surv.data <- cbind(surv.time,cens.ind) event.data <- event.convert(surv.data) event.chart(cbind(rep(0,5),event.data),x.julian=TRUE,x.reference=1)
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