Simple linear spline

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.

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

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)
#> Analysis of Deviance Table
#>  Cox model: response is  Surv(time, status == 9)
#>  Model 1: ~ age + vf + chf + wmi
#>  Model 2: ~ age + wmi + vf + chf + wmi.spline1 + wmi.spline2 + wmi.spline3
#>    loglik  Chisq Df Pr(>|Chi|)    
#> 1 -6529.8                         
#> 2 -6519.6 20.323  3  0.0001455 ***
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

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")