summary.msfit: Summary method for an msfit object

In hputter/mstate: Data Preparation, Estimation and Prediction in Multi-State Models

Summary method for an msfit object

Description

Summary method for an object of class 'msfit'. It prints a selection of the estimated cumulative transition intensities, and, if requested, also of the (co)variances.

Usage

## S3 method for class 'msfit'
summary(
  object,
  times,
  transitions,
  variance = TRUE,
  conf.int = 0.95,
  conf.type = c("log", "none", "plain"),
  extend = FALSE,
  ...
)

Arguments

object	Object of class 'msfit', containing estimated cumulative transition intensities for all transitions in a multi-state model
times	Time points at which to evaluate the cumulative transition hazards
transitions	The transition for which to summarize the cumulative transition hazards
variance	Whether or not the standard errors of the estimated cumulative transition intensities should be printed; default is TRUE
conf.int	The proportion to be covered by the confidence intervals, default is 0.95
conf.type	The type of confidence interval, one of "log", "none", or "plain". Defaults to "log"
extend	logical value: if TRUE, prints information for all specified times, even if there are no subjects left at the end of the specified times. This is only valid if the times argument is present
...	Further arguments to summary

Value

Function summary.msfit returns an object of class "summary.msfit", which is a list (for each from state) of cumulative transition hazaards at the specified (or all) time points. The print method of a summary.probtrans doesn't return a value.

Author(s)

Hein Putter [e-mail]

See Also

msfit

Examples

# Start with example from msfit
tmat <- trans.illdeath()
tg <- data.frame(illt=c(1,1,6,6,8,9),ills=c(1,0,1,1,0,1),
                 dt=c(5,1,9,7,8,12),ds=c(1,1,1,1,1,1),
                 x1=c(1,1,1,0,0,0),x2=c(6:1))
tglong <- msprep(time=c(NA,"illt","dt"),status=c(NA,"ills","ds"),
                 data=tg,keep=c("x1","x2"),trans=tmat)
tglong <- expand.covs(tglong,c("x1","x2"))
cx <- coxph(Surv(Tstart,Tstop,status)~x1.1+x2.2+strata(trans),
            data=tglong,method="breslow")
newdata <- data.frame(trans=1:3,x1.1=c(0,0,0),x2.2=c(0,1,0),strata=1:3)
msf <- msfit(cx,newdata,trans=tmat)

# Default, all transitions, with SE
summary(msf)
summary(msf, conf.type="plain")
# Only transitions 1 and 3
summary(msf, tra=c(1, 3))
# Default is 95% confidence interval, change here to 90% 
summary(msf, conf.int=0.90)
# Do not show variances (nor confidence intervals)
summary(msf, variance=FALSE)
# Cumulative hazards only at specified time points
summary(msf, times=seq(0, 15, by=3))
# Last specified time point is larger than last observed, not printed
# Use extend=TRUE as in summary.survfit
summary(msf, times=seq(0, 15, by=3), extend=TRUE)
# Different types of confidence intervals, default is log
summary(msf, times=seq(0, 15, by=3), conf.type="plain")
summary(msf, times=seq(0, 15, by=3), conf.type="no")
# When the number of time points specified is larger than 12, head and tail is shown
x <- summary(msf, times=seq(5, 8, by=0.25))
x

hputter/mstate documentation built on Dec. 2, 2024, 8:16 p.m.