plot.icfit: Plot icfit object

In interval: Weighted Logrank Tests and NPMLE for Interval Censored Data

Plot icfit object

Description

Plots either the survival distributions, the cumulative distributions, or a transformation of the cumulative distributions, from an icfit object. If there is more than one strata, all strata will be plotted. Note that for interval censored data, the changes in the NPMLE of the survival function usually do not occur at unique points but occur within some interval where any of an infinite number of curves will maximize the likelihood. We show those intervals were the NPMLE is indeterminate as a gray rectangle.

Usage

## S3 method for class 'icfit'
plot(x,XLAB="time",YLAB=NULL,COL=gray((8:1)*.1),LTY=1:9,LEGEND=NULL,
    XLEG=NULL,YLEG=NULL,shade=TRUE,dtype="survival",
    dlink=function(x){log(-log(1-x))}, xscale=1, yscale=1, conf.int=NULL,
    estpar=list( lty=NULL, lwd=1, col=gray(0)),
    cipar=list( lty=1:9, lwd=1, col=gray(0.8)),
    ...)

Arguments

x	an icfit object, see icfit
XLAB	x label
YLAB	y label, if NULL label matches dtype
COL	a vector representing color of rectangles of indeterminate NPMLE, COL[i] used for ith strata
LTY	a vector for lty values for lines, LTY[i] used for ith strata
LEGEND	logical value, include legend or not, if NULL set to TRUE only if number of strata>1
XLEG	x location for legend, if NULL then gives maximum of 0 and minimum time from intmap
YLEG	y location for legend
shade	logical, should the rectangles of indeterminate NPMLE be colored?
dtype	type of distribution plotted, one of 'survival', 'cdf' or 'link' (see details)
dlink	link function when dtype='link' (see details)
xscale	a numeric value used to multiply the labels on the x axis. So if the data are in days, then a value of 1/365.25 would give labels in years.
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. As in the survival package, only the labels are changed, not the actual plot coordinates
conf.int	logical, should confidence intervals be plotted? NULL plots them if they are present in x object and gives no errors if they are not.
estpar	list of par arguments for the estimated distribution lines. If lty=NULL uses LTY argument, otherwise ignores LTY (for backward compatability)
cipar	list of par arguments for the confidence interval lines
...	other arguments passed to the plot function

Details

Turnbull (1976) noted that the NPMLE was not unique within a certain set of intervals. We represent that non-uniqueness using colored rectangles when shade=TRUE. The option shade=TRUE is not supported when dtype="link".

The option dtype="cdf" plots the cumulative distribution function.

When there are several strata, different types of weighted logrank-type tests (see ictest) may be derived from score statistics under the grouped continuous model with error distribution known. To test which test is appropriate, one may plot the cumulative distribution for each stratum transformed by the inverse of the proposed error distribution (see Fay, 1996). These are plotted with dtype="link" where dlink is the link function which transforms the cdf. The "wmw" scores correspond to dlink=qlogis, the "logrank2" scores correspond to the default complementary log-log dlink, and the "normal" scores correspond to dlink=qnorm.

Value

Returns a list of arguments for the legend. Values are x,y, legend, fill, lty. See legend help.

Note

An object of class 'icsurv' from the Icens package can use this plot function by redefining its class to 'icfit' and 'plot.icfit' will work on it.

References

Fay, MP (1996). Rank invariant tests for interval censored data under the grouped continuous model. Biometrics. 52: 811-822.

Turnbull, B.W. (1976) The empirical distribution function with arbitrarily grouped, censored and truncated data. J. R. Statist. Soc. B 38, 290-295.

See Also

icfit

Examples

data(bcos)
fit1<-icfit(Surv(left,right,type="interval2")~treatment,data=bcos)
summary(fit1)
plot(fit1)
 

interval documentation built on Aug. 25, 2023, 1:08 a.m.