mstate: summary.msfit – R documentation

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summary.msfit

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 H.Putter@lumc.nl

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

mstate

Data Preparation, Estimation and Prediction in Multi-State Models

v0.3.1

GPL (>= 2)

Authors

Hein Putter [aut, cre], Liesbeth C. de Wreede [aut], Marta Fiocco [aut], Ronald B. Geskus [ctb], Edouard F. Bonneville [ctb], Damjan Manevski [ctb]

Initial release

2020-12-17