`survfit`

objectsA plot of survival curves is produced, one curve for each strata.
The `log=T`

option does extra work to avoid log(0), and to try to create a
pleasing result. If there are zeros, they are plotted by default at
0.8 times the smallest non-zero value on the curve(s).

Curves are plotted in the same order as they are listed by `print`

(which gives a 1 line summary of each).
This will be the order in which `col`

, `lty`

, etc are used.

```
# S3 method for survfit
plot(x, conf.int=, mark.time=FALSE,
pch=3, col=1, lty=1, lwd=1, cex=1, log=FALSE, xscale=1, yscale=1,
firstx=0, firsty=1, xmax, ymin=0, fun,
xlab="", ylab="", xaxs="S", conf.times, conf.cap=.005,
conf.offset=.012, mark, …)
```

x

an object of class `survfit`

, usually returned by the
`survfit`

function.

conf.int

determines whether confidence intervals will be plotted. The default is to do so if there is only 1 curve, i.e., no strata.

mark.time

controls the labeling of the curves. If set to `FALSE`

, no
labeling is done.
If `TRUE`

, then curves are marked at each censoring time.
If `mark`

is a
numeric vector then curves are marked at the specified time points.

pch

vector of characters which will be used to label the curves.
The `points`

help file contains examples of the possible marks.
A single string such as "abcd" is treated as a vector
`c("a", "b", "c", "d")`

.
The vector is reused cyclically if it is shorter than the number of
curves. If it is present this implies `mark.time = TRUE`

.

col

a vector of integers specifying colors for each curve. The default value is 1.

lty

a vector of integers specifying line types for each curve. The default value is 1.

lwd

a vector of numeric values for line widths. The default value is 1.

cex

a numeric value specifying the size of the marks. This is not treated as a vector; all marks have the same size.

log

a logical value, if TRUE the y axis wll be on a log scale. Alternately, one of the standard character strings "x", "y", or "xy" can be given to specific logarithmic horizontal and/or vertical axes.

yscale

a numeric value used to multiply the labels on the y axis.
A value of 100, for instance, would be used to give a percent scale.
Only the labels are
changed, not the actual plot coordinates, so that adding a curve with
"`lines(surv.exp(...))`

", say,
will perform as it did without the `yscale`

argument.

xscale

a numeric value used like `yscale`

for labels on the x axis.
A value of 365.25 will give labels in years instead of the original days.

firstx, firsty

the starting point for the survival curves. If either of these is set to
`NA`

the plot will start at the first time point of the curve.
By default, the plot program obeys tradition by having the plot start at
(0,0).

If `start.time`

argument is used in `survfit`

, `firstx`

is set to that value.

xmax

the maximum horizontal plot coordinate. This can be used to shrink
the range of a plot. It shortens the curve before plotting it, so
that unlike using the `xlim`

graphical parameter, warning
messages about out of bounds points are not generated.

ymin

lower boundary for y values. Survival curves are most often drawn in the
range of 0-1, even if none of the curves approach zero.
The parameter is ignored if the `fun`

argument is present,
or if it has been set to `NA`

.

fun

an arbitrary function defining a transformation of the survival curve.
For example `fun=log`

is an alternative way to draw a log-survival curve
(but with the axis labeled with log(S) values),
and `fun=sqrt`

would generate a curve on square root scale.
Four often used transformations can be specified with a character
argument instead: `"log"`

is the same as using the `log=T`

option,
`"event"`

plots cumulative events (f(y) = 1-y),
`"cumhaz"`

plots the cumulative hazard function (f(y) = -log(y)), and
`"cloglog"`

creates a complimentary log-log survival plot (f(y) =
log(-log(y)) along with log scale for the x-axis).

xlab

label given to the x-axis.

ylab

label given to the y-axis.

xaxs

either `"S"`

for a survival curve or a standard x axis style as
listed in `par`

.
Survival curves are usually displayed with the curve touching the y-axis,
but not touching the bounding box of the plot on the other 3 sides.
Type `"S"`

accomplishes this by manipulating the plot range and
then using the `"i"`

style internally.

conf.times

optional vector of times at which to place a confidence bar on the curve(s). If present, these will be used instead of confidence bands.

conf.cap

width of the horizontal cap on top of the confidence bars; only used if conf.times is used. A value of 1 is the width of the plot region.

conf.offset

the offset for confidence bars, when there are multiple curves on the plot. A value of 1 is the width of the plot region. If this is a single number then each curve's bars are offset by this amount from the prior curve's bars, if it is a vector the values are used directly.

mark

a historical alias for `pch`

…

for future methods

a list with components `x`

and `y`

, containing the coordinates of the last point
on each of the curves (but not the confidence limits).
This may be useful for labeling.

When the `survfit`

function creates a multi-state survival curve
the resulting object also has class `survfitms'.
Competing risk curves are a common case. The only difference in
the plots is that multi-state defaults to a curve that goes from lower
left to upper right (starting at 0), where survival curves by default
start at 1 and go down. All other options are identical.

When the `conf.times`

argument is used, the confidence bars are
offset by `conf.offset`

units to avoid overlap.
The bar on each curve are the confidence interval for the time point
at which the bar is drawn, i.e., different time points for each curve.
If curves are steep at that point, the visual impact can sometimes
substantially differ for positive and negative values of
`conf.offset`

.

```
# NOT RUN {
leukemia.surv <- survfit(Surv(time, status) ~ x, data = aml)
plot(leukemia.surv, lty = 2:3)
legend(100, .9, c("Maintenance", "No Maintenance"), lty = 2:3)
title("Kaplan-Meier Curves\nfor AML Maintenance Study")
lsurv2 <- survfit(Surv(time, status) ~ x, aml, type='fleming')
plot(lsurv2, lty=2:3, fun="cumhaz",
xlab="Months", ylab="Cumulative Hazard")
# }
```

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