kaps (version 0.8.3)

lrtree: Recursive partitioning for censored survival data by log-rank test

Description

Conduct recursive partitioning algorithm for censored survival data by log-rank related tests.

Usage

lrtree(Formula, data, subset = NULL, weights = NULL, ...)

Arguments

Formula

an object with the type of Formula, with the response of the left hand side of the '~' operator, and the covariate terms on the right side. The response have be a survival object with survival time and censoring status by Surv. See

data

a dataset with variables used in Formula. It needs at least three variables including survival time, censoring status, and a covariate. The structure of this object is data.frame.

subset

an optional vector to be used as a subset of observations.

weights

an optional vector to be used as a weight parameter.

...

a S4 class object specifying minior parameters for lrtree() using lrtree.control

See Also

km.curve, labels, plot, show, summary, text for the convenient use of lrtree lrtree.control to control lrtree more detail kaps, apss.control for counterpart of the lrtree

Examples

## toy example
data(toy)
f <- Surv(time, status) ~ meta
fit <- lrtree(f, data = toy, B = 20)
### Print lrtree object
fit
### Print survival median time, 1 years, 3 years, and 5 years times. 
summary(fit)

### Plot tree diagram
plot(fit) # type = "naive"

### Plot Kaplan-Meire survival curves for terminal nodes.
km.curve(fit)

#f <- Surv(time, status) ~ ratio
#fit <- lrtree(f, data = toy, minbucket = 100, pre.pt = seq(0, 0.95, by = .05))
#plot(fit, type = "naive") # type = "naive"
### Print survival median time, i years, 3 years, and 5 years times by summary(). 
#summary(fit)

### Draw Kaplan-Meier survival curves
#km.curve(fit)
#legend(120,0.6, col=c(1:6)[fit.order],  lwd=2, 
#		   c("Node 8  (0.00 <= Ratio <= 0.10)",
#			 "Node 11 (0.45 <  Ratio <= 0.75)",
#			 "Node 3  (0.75 <  Ratio <= 1.00)"),
#		   bty="n")