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survival (version 3.6-4)

plot.cox.zph: Graphical Test of Proportional Hazards

Description

Displays a graph of the scaled Schoenfeld residuals, along with a smooth curve.

Usage

# S3 method for cox.zph
plot(x, resid=TRUE, se=TRUE, df=4, nsmo=40, var,
        xlab="Time", ylab, lty=1:2, col=1, lwd=1, hr=FALSE, plot=TRUE, ...)

Arguments

x

result of the cox.zph function.

resid

a logical value, if TRUE the residuals are included on the plot, as well as the smooth fit.

se

a logical value, if TRUE, confidence bands at two standard errors will be added.

df

the degrees of freedom for the fitted natural spline, df=2 leads to a linear fit.

nsmo

number of points to use for the lines

var

the set of variables for which plots are desired. By default, plots are produced in turn for each variable of a model. Selection of a single variable allows other features to be added to the plot, e.g., a horizontal line at zero or a main title.

This has been superseded by a subscripting method; see the example below.

hr

if TRUE, label the y-axis using the estimated hazard ratio rather than the estimated coefficient. (The plot does not change, only the axis label.)

xlab

label for the x-axis of the plot

ylab

optional label for the y-axis of the plot. If missing a default label is provided. This can be a vector of labels.

lty, col, lwd

line type, color, and line width for the overlaid curve. Each of these can be vector of length 2, in which case the second element is used for the confidence interval.

plot

if FALSE, return a list containing the x and y values of the curve, instead of drawing a plot

...

additional graphical arguments passed to the plot function.

Side Effects

a plot is produced on the current graphics device.

See Also

coxph, cox.zph.

Examples

Run this code
vfit <- coxph(Surv(time,status) ~ trt + factor(celltype) + 
              karno + age, data=veteran, x=TRUE) 
temp <- cox.zph(vfit) 
plot(temp, var=3)      # Look at Karnofsy score, old way of doing plot 
plot(temp[3])     # New way with subscripting 
abline(0, 0, lty=3) 
# Add the linear fit as well  
abline(lm(temp$y[,3] ~ temp$x)$coefficients, lty=4, col=3)  
title(main="VA Lung Study") 

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