dspline: Simple linear spline

In mets: Analysis of Multivariate Event Times

Simple linear spline

Description

Constructs simple linear spline on a data frame using the formula syntax of dutils that is adds (x-cuti)* (x>cuti) to the data-set for each knot of the spline. The full spline is thus given by x and spline variables added to the data-set.

Usage

dspline(
  data,
  y = NULL,
  x = NULL,
  breaks = 4,
  probs = NULL,
  equi = FALSE,
  regex = mets.options()$regex,
  sep = NULL,
  na.rm = TRUE,
  labels = NULL,
  all = FALSE,
  ...
)

Arguments

data	if x is formula or names for data frame then data frame is needed.
y	name of variable, or fomula, or names of variables on data frame.
x	name of variable, or fomula, or names of variables on data frame.
breaks	number of breaks, for variables or vector of break points,
probs	groups defined from quantiles
equi	for equi-spaced breaks
regex	for regular expressions.
sep	seperator for naming of cut names.
na.rm	to remove NA for grouping variables.
labels	to use for cut groups
all	to do all variables, even when breaks are not unique
...	Optional additional arguments

Author(s)

Thomas Scheike

Examples

data(TRACE)
TRACE <- dspline(TRACE,~wmi,breaks=c(1,1.3,1.7))
cca <- coxph(Surv(time,status==9)~age+vf+chf+wmi,data=TRACE)
cca2 <- coxph(Surv(time,status==9)~age+wmi+vf+chf+wmi.spline1+wmi.spline2+wmi.spline3,data=TRACE)
anova(cca,cca2)

nd=data.frame(age=50,vf=0,chf=0,wmi=seq(0.4,3,by=0.01))
nd <- dspline(nd,~wmi,breaks=c(1,1.3,1.7))
pl <- predict(cca2,newdata=nd)
plot(nd$wmi,pl,type="l")

mets documentation built on May 29, 2024, 3:51 a.m.