R: Landmark Aalen-Johansen method

LMAJ {mstate} | R Documentation

## Landmark Aalen-Johansen method

### Description

This function implements the landmark Aalen-Johansen method of Putter & Spitoni (2016) for non-parametric estimation of transition probabilities in non-Markov models.

### Usage

    LMAJ(msdata, s, from, method=c("aalen", "greenwood"))

### Arguments

`msdata` | An `"msdata"` object, as for instance prepared by `link{msprep}`
`s` | The prediction time point s from which transition probabilities are to be obtained
`from` | Either a single state or a set of states in the state space 1,...,S
`method` | The method for calculating variances, as in `probtrans`

### Value

A data frame containing estimates and associated standard errors of the transition probabilities P(X(t)=k | X(s) in `from`) with `s` and `from` the arguments of the function.

### Author(s)

Hein Putter H.Putter@lumc.nl

### References

H. Putter and C. Spitoni (2016). Estimators of transition probabilities in non-Markov multi-state models. Submitted.

### Examples

    data(prothr)
    tmat <- attr(prothr, "trans")
    pr0 <- subset(prothr, treat=="Placebo")
    attr(pr0, "trans") <- tmat
    pr1 <- subset(prothr, treat=="Prednisone")
    attr(pr1, "trans") <- tmat
    c0 <- coxph(Surv(Tstart, Tstop, status) ~ strata(trans), data=pr0)
    c1 <- coxph(Surv(Tstart, Tstop, status) ~ strata(trans), data=pr1)
    msf0 <- msfit(c0, trans=tmat)
    msf1 <- msfit(c1, trans=tmat)
    # Comparison as in Figure 2 of Titman (2015)
    # Aalen-Johansen
    pt0 <- probtrans(msf0, predt=1000)[[2]]
    pt1 <- probtrans(msf1, predt=1000)[[2]]
    par(mfrow=c(1,2))
    plot(pt0$time, pt0$pstate1, type="s", lwd=2, xlim=c(1000,4000), ylim=c(0,0.61),
         xlab="Time since randomisation (days)", ylab="Probability")
    lines(pt1$time, pt1$pstate1, type="s", lwd=2, lty=3)
    legend("topright", c("Placebo", "Prednisone"), lwd=2, lty=1:2, bty="n")
    title(main="Aalen-Johansen")
    # Landmark Aalen-Johansen
    LMpt0 <- LMAJ(msdata=pr0, s=1000, from=2)
    LMpt1 <- LMAJ(msdata=pr1, s=1000, from=2)
    plot(LMpt0$time, LMpt0$pstate1, type="s", lwd=2, xlim=c(1000,4000), ylim=c(0,0.61),
         xlab="Time since randomisation (days)", ylab="Probability")
    lines(LMpt1$time, LMpt1$pstate1, type="s", lwd=2, lty=3)
    legend("topright", c("Placebo", "Prednisone"), lwd=2, lty=1:2, bty="n")
    title(main="Landmark Aalen-Johansen")

[Package mstate version 0.2.12 Index]