sir.cont {mvna} | R Documentation |
Time-dependent ventilation status for intensive care unit (ICU) patients, a random sample from the SIR-3 study.
data(sir.cont)
A data frame with 1161 rows and 4 columns:
The possible states are:
0: No ventilation
1: Ventilation
2: End of stay.
And cens
stands for censored observations.
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.
Beyersmann, J., Gastmeier, P., Grundmann, H., Baerwolff, S., Geffers, C., Behnke, M., Rueden, H., and Schumacher, M. Use of multistate models to assess prolongation of intensive care unit stay due to nosocomial infection. Infection Control and Hospital Epidemiology, 27:493-499, 2006.
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") 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")