event.chart: Flexible Event Chart for Time-to-Event Data
In harrelfe/Hmisc: Harrell Miscellaneous
event.chart R Documentation
Flexible Event Chart for Time-to-Event Data
Description
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.
Usage
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,
...)
Arguments
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., treatment.arm == 'a', if
the data frame, data, has been attached to the search directory;
otherwise, data$treatment.arm == "a").
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., c('randdate', 'event1').
sort.by
column(s) or data frame variable name(s) with which to sort the chart's output.
The default is NA, thereby resulting in a chart sorted by original row number.
sort.ascending
logical flag (which takes effect only if the argument sort.by is utilized).
If TRUE (default), sorting is done in ascending order; if FALSE, descending order.
sort.na.last
logical flag (which takes effect only if the argument sort.by is utilized).
If TRUE (default), NA values are considered as last values in ordering.
sort.after.subset
logical flag (which takes effect only if the argument sort.by is utilized).
If FALSE, sorting data (via sort.by specified variables
or columns) will be performed prior to row subsetting (via subset.r);
if TRUE (default), row subsetting of original data will be done before sorting.
y.var
variable name or column number of original matrix or data frame with
which to scale y-axis.
Default is NA, which will result in equally spaced lines on y-axis
(based on original data or sorted data if requested by sort.by).
Otherwise, location of lines on y-axis will be dictated by specified variable
or column. Examples of specified variables may be date of an event
or a physiological covariate. Any observation which has
a missing value for the y.var variable will not appear on the graph.
y.var.type
type of variable specified in y.var (which will only take effect if
argument y.var is utilized). If "d", specifed variable is a date (either
numeric julian date or an S-Plus dates object); if "n", specifed variable
is numeric (e.g., systolic blood pressure level) although not a julian date.
y.jitter
logical flag (which takes effect only if the argument y.var is utilized).
Due to potential ties in y.var variable, y.jitter (when TRUE) will jitter
the data to allow discrimination between observations at the possible cost
of producing slightly inaccurate dates or covariate values; if FALSE (the
default), no jittering will be performed. The y.jitter algorithm
assumes a uniform distribution of observations across the range of y.var.
The algorithm is as follows:
size.jitter <-
( diff(range(y.var)) / (2 * (length(y.var) - 1)) ) * y.jitter.factor
The default of y.jitter.factor is 1. The entire product is then used as an
argument into runif: y.var <-
y.var + runif(length(y.var), -size.jitter, size.jitter)
y.jitter.factor
an argument used with the y.jitter function to scale the range of added noise.
Default is 1.
y.renum
logical flag. If TRUE, subset observations are listed on y-axis from
1 to length(subset.r); if FALSE (default), subset observations are listed
on y-axis in original form. As an example, if subset.r = 301:340 and
y.renum ==TRUE, y-axis will be shown as 1 through 40. However, if
y.renum ==FALSE, y-axis will be shown as 301 through 340. The above examples
assume the following argument, NA.rm, is set to FALSE.
NA.rm
logical flag. If TRUE, subset observations which have
NA for each variable specified in subset.c will not have an
entry on the y-axis. Also, if the following argument,
x.reference, is specified, observations with missing
x.reference values will also not have an entry on the y-axis.
If FALSE (default), user can identify those observations
which do have NA for every variable specified in
subset.c (or, if x.reference is specified, also
those observations which are missing only the x.reference value); this can
easily be done by examining the resulting y-axis and
recognizing the observations without any plotting symbols.
x.reference
column of original matrix or data frame with which to reference the x-axis.
That is, if specified, all columns specified in subset.c will be substracted
by x.reference. An example may be to see the timing of events before and
after treatment or to see time-to-event after entry into study.
The event times will be aligned using the x.reference argument
as the reference point.
now
the “now” date which will be used for top of y-axis
when creating the Goldman eventchart (see reference below).
Default is max(data[, subset.c], na.rm =TRUE).
now.line
logical flag. A feature utilized by the Goldman Eventchart.
When x.reference is specified as the start of follow-up and
y.var = x.reference, then the Goldman chart can be created.
This argument, if TRUE, will cause the plot region to be square, and will
draw a line with a slope of -1 from the top of the y-axis to the right
end of the x-axis. Essentially, it denotes end of current follow-up period
for looking at the time-to-event data. Default is FALSE.
now.line.lty
line type of now.line.
now.line.lwd
line width of now.line.
now.line.col
color of now.line.
pty
graph option, pty='m' is the default; use pty='s' for the square looking
Goldman's event chart.
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
y.julian = FALSE or x.julian = FALSE.
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 c('pt.no') is specified, patient ID (stored in pt.no)
will be seen on y-axis labels
instead of sequence specified by subset.r. This argument takes precedence
over both y.axis = 'auto' and y.axis = 'custom' (see below).
NOTE: Program will issue warning if this argument is
specified and if is.na(y.var) == FALSE; y.idlabels will not be
used in this situation. Also, attempting to plot too many patients
on a single event chart will cause undesirable plotting of y.idlabels.
y.axis
character string specifying whether program will control labelling
of y-axis (with argument "auto"), or if user will control labelling
(with argument "custom"). If "custom" is chosen, user must specify
location and text of labels using y.axis.custom.at and
y.axis.custom.labels arguments, respectively, listed below.
This argument will not be utilized if y.idlabels is specified.
y.axis.custom.at
user-specified vector of y-axis label locations.
Must be used when y.axis = "custom"; will not be used otherwise.
y.axis.custom.labels
user-specified vector of y-axis labels.
Must be used when y.axis = "custom"; will not be used otherwise.
y.julian
logical flag (which will only be considered if y.axis == "auto" and
(!is.na(y.var) & y.var.type== "d"). If FALSE (default), will convert julian
numeric dates or S-Plus dates objects into “mm/dd/yy” format
for the y-axis labels. If TRUE, dates will be printed in
julian (numeric) format.
y.lim.extend
two-dimensional vector representing the number of units that the user
wants to increase ylim on bottom and top of y-axis, respectively.
Default c(0,0). This argument will not take effect if the Goldman chart
is utilized.
y.lab
single label to be used for entire y-axis. Default will be the variable name
or column number of y.idlabels (if non-missing) and blank otherwise.
x.axis.all
logical flag. If TRUE (default), lower and upper limits of x-axis will be
based on all observations (rows) in matrix or data frame. If FALSE, lower and
upper limits will be based only on those observations specified by subset.r
(either before or after sorting depending on specification of sort.by and
value of sort.after.subset).
x.axis
character string specifying whether program will control labelling
of x-axis (with argument "auto"), or if user will control labelling
(with argument "custom"). If "custom" is chosen, user must specify
location and text of labels using x.axis.custom.at and
x.axis.custom.labels arguments, respectively, listed below.
x.axis.custom.at
user-specified vector of x-axis label locations.
Must be used when x.axis == "custom"; will not be used otherwise.
x.axis.custom.labels
user-specified vector of x-axis labels.
Must be used when x.axis == "custom"; will not be used otherwise.
x.julian
logical flag (which will only be considered if x.axis == "auto").
If FALSE (default), will convert julian dates or S-plus dates objects
into “mm/dd/yy” format for the x-axis labels. If TRUE, dates will be
printed in julian (numeric) format. NOTE: This argument should remain TRUE if
x.reference is specified.
x.lim.extend
two-dimensional vector representing the number of time units (usually in days)
that the user wants to increase xlim on left-hand side and right-hand
side of x-axis, respectively. Default is c(0,0). This argument will not
take effect if the Goldman chart is utilized.
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.scale = 365 will result in units of years (notwithstanding leap years).
Default is 1.
x.lab
single label to be used for entire x-axis. Default will be “On Study Date”
if x.julian = FALSE and “Time on Study” if x.julian = TRUE.
line.by
column or data frame variable name for plotting unique lines by unique
values of vector (e.g., specify c('arm') to plot unique lines by
treatment arm). Can take at most one column or variable name.
Default is NA which produces identical lines for each patient.
line.lty
vector of line types corresponding to ascending order of line.by values.
If line.by is specified, the vector should be the length of
the number of unique values of line.by.
If line.by is NA, only line.lty[1] will be used.
The default is 1.
line.lwd
vector of line widths corresponding to ascending order of line.by values.
If line.by is specified, the vector should be the length of
the number of unique values of line.by.
If line.by is NA, only line.lwd[1] will be used.
The default is 1.
line.col
vector of line colors corresponding to ascending order of line.by values.
If line.by is specified, the vector should be the length of
the number of unique values of line.by.
If line.by is NA, only line.col[1] will be used.
The default is 1.
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 line.add argument would be
matrix(c('first.event','second.event','second.event','third.event',
'fourth.event','fifth.event'), 2, 3). One line segment
would be drawn between first.event and second.event,
a second line segment would be drawn between second.event and third.event,
and a third line segment would be drawn between fourth.event and fifth.event.
Different line types, widths and colors can be specified (in arguments
listed just below).
The convention use of subset.c and line.add must match (i.e., column name
must be used for both or column number must be used for both).
If line.add != NA, length of line.add.lty, line.add.lwd, and line.add.col
must be the same as number of pairs of additional line segments to add.
NOTE: The drawing of the original default line
may be suppressed (with line.col = 0),
and line.add can be used to do all the line plotting for the event chart.
line.add.lty
a kx1 vector corresponding to the columns of line.add; specifies the line
types for the k line segments.
line.add.lwd
a kx1 vector corresponding to the columns of line.add; specifies the line
widths for the k line segments.
line.add.col
a kx1 vector corresponding to the columns of line.add; specifies the line
colors for the k line segments.
point.pch
vector of pch values for points representing each event. If similar
events are listed in multiple columns (e.g., regular visits or
a recurrent event), repeated pch values may be listed in the
vector (e.g., c(2,4,rep(183,3))).
If length(point.pch) < length(subset.c), point.pch will be repeated until
lengths are equal; a warning message will verify this condition.
point.cex
vector of size of points representing each event.
If length(point.cex) < length(subset.c), point.cex will be repeated until
lengths are equal; a warning message will verify this condition.
point.col
vector of colors of points representing each event.
If length(point.col) < length(subset.c), point.col will be repeated until
lengths are equal; a warning message will verify this condition.
point.cex.mult
a single number (may be non-integer), which is the base multiplier for the value of
the cex of the plotted points, when interest lies in
a variable size allowed for certain points, as a function of
the quantity of the variable(s) in the dataset specified in the point.cex.mult.var argument;
multiplied by original point.cex value and then the value of interest (for an individual)
from the point.cex.mult.var argument;
used only when non-NA arguments are provided to point.cex.mult.var;
default is 1. .
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)
subset.c variables, when interest lies in
a variable size allowed for certain points, as a function of
the level of some variable(s) in the dataset;
default is NA.
extra.points.no.mult
vector of variables in the dataset to ignore for purposes of using
point.cex.mult; for example, for some variables there may be interest in
allowing a variable size allowed for the plotting of the points, whereas
other variables (e.g., dropout time), there may be no interest in such manipulation;
the vector should be the same size as the number of variables specified in subset.c,
with NA entries where variable point size is of interest
and the variable name (or location in subset.c) specified when the variable
point size is not of interest; in this latter case,
the associated argument in point.cex is instead used as the point cex;
used only when non-NA arguments are provided to point.cex.mult.var;
default is NA
legend.plot
logical flag; if TRUE, a legend will be plotted. Location of legend will
be based on specification of legend.location along with values of other
arguments listed below. Default is FALSE (i.e., no legend plotting).
legend.location
will be used only if legend.plot = TRUE.
If "o" (default), a one-page legend will precede the output of the chart.
The user will need to hit enter in order for the event chart to be displayed.
This feature is possible due to the dev.ask option.
If "i", an internal legend will be placed in the plot region
based on legend.point.at. If "l", a legend will be placed in the plot region
using the locator option. Legend will map points to events (via column
names, by default) and, if line.by is specified, lines to groups (based on
levels of line.by).
legend.titl
title for the legend; default is title to be used for main plot.
Only used when legend.location = "o".
legend.titl.cex
size of text for legend title. Only used when legend.location = "o".
legend.titl.line
line location of legend title dictated by mtext function with
outer = FALSE option;
default is 1.0. Only used when legend.location = "o".
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 pch values for points representing each event in the legend.
Default is point.pch.
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 subset.c.
legend.cex
size of text for points and event descriptions. Default is 2.5 which is setup
for legend.location = "o". A much smaller cex is recommended (possibly 0.75)
for use with legend.location = "i" or legend.location = "l".
legend.bty
option to put a box around the legend(s); default is to have no box
(legend.bty = "n"). Option legend.bty = "o" will produce a legend box.
legend.line.at
if line.by was specified (with legend.location = "o" or legend.location = "i"),
this argument will dictate the location of the upper left and lower right
corners of legend area to be utilized for describing the different
line.by values (e.g., treatment.arm). The default is setup for
legend.location = "o".
legend.line.text
text to be used for describing line.by values; the default are the names
of the unique non-missing line.by values as produced from the table function.
legend.line.lwd
vector of line widths corresponding to line.by values.
legend.loc.num
number used for locator argument when legend.locator = "l". If 1 (default),
user is to locate only the top left corner of the legend box. If 2, user
is to locate both the top left corner and the lower right corner. This will
be done twice when line.by is specified (once for points and once for lines).
...
additional par arguments for use in main plot.
Details
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.
Side Effects
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.
Author(s)
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
References
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.
See Also
event.history, Date
Examples
# 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)
harrelfe/Hmisc documentation built on Nov. 21, 2024, 3:47 p.m.
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| event.chart | R Documentation |
Flexible Event Chart for Time-to-Event Data
Description
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.
Usage
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,
...)
Arguments
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. |
Details
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.
Side Effects
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.
Author(s)
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
References
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.
See Also
event.history, Date
Examples
# 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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