R: Expected length of stay

ELOS {mstate} | R Documentation

## Expected length of stay

### Description

Given a `"probtrans"` object, ELOS calculates the (restricted) expected length of stay in each of the states of the multi-state model.

### Usage

    ELOS(pt, tau)

### Arguments

`pt` | An object of class `"probtrans"`
`tau` | The horizon until which ELOS is calculated; if missing, the maximum of the observed transition times is taken

### Details

The object `pt` needs to be a `"probtrans"` object, obtained with forward prediction (the default, `direction`=`"forward"`, in the call to `probtrans`). The restriction to `tau` is there because, as in ordinary survival analysis, the probability of being in a state can be positive until infinity, resulting in infinite values. The (restricted, until tau) expected length of stay in state h, given in state g at time s, is given by the integral from s to tau of P_gh(s,t), see for instance Beyersmann and Putter (2014).

### Value

A K x K matrix (with K number of states), with the (g,h)'th element containing E_gh(s,tau). The starting time point s is inferred from `pt` (the smallest time point, should be equal to the `predt` value in the call to `probtrans`. The row- and column names of the matrix have been named "from1" until "fromK" and "in1" until "inK", respectively.

### Author(s)

Hein Putter H.Putter@lumc.nl

### Examples

    # transition matrix for illness-death model
    tmat <- trans.illdeath()
    # data in wide format, for transition 1 this is dataset E1 of
    # Therneau & Grambsch (2000)
    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))
    # data in long format using msprep
    tglong <- msprep(time=c(NA,"illt","dt"),status=c(NA,"ills","ds"),
    		data=tg,keep=c("x1","x2"),trans=tmat)
    # events
    events(tglong)
    table(tglong$status,tglong$to,tglong$from)
    # expanded covariates
    tglong <- expand.covs(tglong,c("x1","x2"))
    # Cox model with different covariate
    cx <- coxph(Surv(Tstart,Tstop,status)~x1.1+x2.2+strata(trans),
            data=tglong,method="breslow")
    summary(cx)
    # new data, to check whether results are the same for transition 1 as
    # those in appendix E.1 of Therneau & Grambsch (2000)
    newdata <- data.frame(trans=1:3,x1.1=c(0,0,0),x2.2=c(0,1,0),strata=1:3)
    HvH <- msfit(cx,newdata,trans=tmat)
    # probtrans
    pt <- probtrans(HvH,predt=0)
    # ELOS until last observed time point
    ELOS(pt)
    # Restricted ELOS until tau=10
    ELOS(pt, tau=10)

[Package mstate version 0.3.2 Index]