Draw predicted survival curve as a ggplot with an object survreg

Usage

adjustedPlot2.survreg(
  x,
  xnames = NULL,
  pred.values = list(),
  maxy.lev = 5,
  newdata = NULL,
  addCox = FALSE,
  autovar = TRUE,
  legend.position = NULL,
  facet = NULL
)

Arguments

x: An object of class survreg
xnames: Character Names of explanatory variable to plot
pred.values: A list A list of predictor values
maxy.lev: Integer Maximum unique length of a numeric variable to be treated as categorical variables
newdata: A data.frame or NULL
addCox: logical Whether or not add KM
autovar: logical
legend.position: Character Default value is "topright"
facet: Character name(s) of facet variable(s)

Value

A ggplot

Examples

library(survival)
x=survreg(Surv(time, status) ~ rx, data=anderson,dist="exponential")
adjustedPlot(x,type="plot")

adjustedPlot(x)

adjustedPlot(x,addCox=TRUE)
#> Warning: Removed 42 rows containing missing values (`geom_line()`).

if (FALSE) {
x=survreg(Surv(time, status) ~ sex, data=lung,dist="weibull")
adjustedPlot(x,addCox=TRUE)
x=survreg(Surv(time, status) ~ rx, data=anderson,dist="exponential")
adjustedPlot(x,addCox=TRUE)
x=survreg(Surv(time, status) ~ ph.ecog + age + sex, data=lung, dist="weibull")
pred.values=list(ph.ecog=0:3,sex=1:2,age=c(20,40,60,80))
adjustedPlot(x)
adjustedPlot(x,addCox=TRUE)
adjustedPlot(x,addCox=TRUE,xnames=c("ph.ecog","sex"),facet="sex")
adjustedPlot(x,pred.values=pred.values,addCox=TRUE,legend.position="top")+xlim(c(1,1000))
adjustedPlot(x,pred.values=pred.values,xnames=c("ph.ecog","sex","age"),facet=c("ph.ecog","sex"))
adjustedPlot(x,pred.values=pred.values,xnames=c("ph.ecog","sex","age"),facet=c("age","sex"))
adjustedPlot(x,pred.values=pred.values,addCox=TRUE)
adjustedPlot(x,addCox=TRUE)
adjustedPlot(x,pred.values=list(age=c(20,40,60,80),sex=1,ph.ecog=3),addCox=TRUE)
}