mvna (version 2.0.1)

sir.cont: Ventilation status in intensive care unit patients

Description

Time-dependent ventilation status for intensive care unit (ICU) patients, a random sample from the SIR-3 study.

Usage

data(sir.cont)

Format

A data frame with 1141 rows and 6 columns:

id:

Randomly generated patient id

from:

State from which a transition occurs

to:

State to which a transition occurs

time:

Time when a transition occurs

age:

Age at inclusion

sex:

Sex. F for female and M for male

The possible states are:

0: No ventilation

1: Ventilation

2: End of stay.

And cens stands for censored observations.

Details

This data frame consists in a random sample of the SIR-3 cohort data. It focuses on the effect of ventilation on the length of stay (combined endpoint discharge/death). Ventilation status is considered as a transcient state in an illness-death model.

The data frame is directly formated to be used with the mvna function, i.e., it is transition-oriented with one row per transition.

Examples

# NOT RUN {
data(sir.cont)

# Matrix of possible transitions
tra <- matrix(ncol=3,nrow=3,FALSE)
tra[1, 2:3] <- TRUE
tra[2, c(1, 3)] <- TRUE

# Modification for patients entering and leaving a state
# at the same date
sir.cont <- sir.cont[order(sir.cont$id, sir.cont$time), ]
for (i in 2:nrow(sir.cont)) {
  if (sir.cont$id[i]==sir.cont$id[i-1]) {
    if (sir.cont$time[i]==sir.cont$time[i-1]) {
      sir.cont$time[i-1] <- sir.cont$time[i-1] - 0.5
    }
  }
}

# Computation of the Nelson-Aalen estimates
  na.cont <- mvna(sir.cont,c("0","1","2"),tra,"cens")

if (require("lattice")) {
  xyplot(na.cont,tr.choice=c("0 2","1 2"),aspect=1,
       strip=strip.custom(bg="white",
         factor.levels=c("No ventilation -- Discharge/Death",
           "Ventilation -- Discharge/Death"),
         par.strip.text=list(cex=0.9)),
       scales=list(alternating=1),xlab="Days",
       ylab="Nelson-Aalen estimates")
}
# }