plot {JM}R Documentation

Plot Diagnostics for Joint Models

Description

Produces a variety of plots for fitted joint models.

Usage

## S3 method for class 'jointModel':
plot(x, which = 1:4, caption = c("Residuals vs Fitted", 
  "Normal Q-Q", "Marginal Survival", "Marginal Cumulative Hazard", 
  "Marginal log Cumulative Hazard", "Baseline Hazard", 
  "Cumulative Baseline Hazard", "Subject-specific Survival", 
  "Subject-specific Cumulative Hazard", 
  "Subject-specific log Cumulative Hazard"), survTimes = NULL, 
  main = "", 
  ask = prod(par("mfcol")) < length(which) && dev.interactive(), 
  ..., ids = NULL, add.smooth = getOption("add.smooth"), 
  add.qqline = TRUE, add.KM = FALSE, cex.caption = 1)

Arguments

x an object inheriting from class jointModel.
which which types of plots to produce, specify a subset of the numbers 1:10.
caption captions to appear above the plots defined by argument which.
survTimes a vector of survival times for which the survival, cumulative hazard or log cumulative hazard will be computed. Default is seq(minT, maxT, length = 15), where minT and maxT are the minimum and maximum observed survival times, respectively.
main a character string specifying the title in the plot.
ask logical; if TRUE, the user is asked before each plot, see par(ask=.).
... other parameters to be passed through to plotting functions.
ids a numeric vector specifying which subjects, the subject-specific plots will include; default is all subjects.
add.smooth logical; if TRUE a smooth line is superimposed in the "Residuals vs Fitted" plot.
add.qqline logical; if TRUE a qq-line is superimposed in the "Normal Q-Q" plot.
add.KM logical; if TRUE the Kaplan-Meier estimate of the survival function is superimposed in the "Marginal Survival" plot.
cex.caption magnification of captions.

Note

The plots of the baseline hazard and the cumulative baseline hazard are only produced when the joint model has been fitted using method = "ph-GH".

Author(s)

Dimitris Rizopoulos d.rizopoulos@erasmusmc.nl

See Also

jointModel

Examples

# linear mixed model fit
fitLME <- lme(log(serBilir) ~ drug * year, random = ~ 1 | id, data = pbc2)
# survival regression fit
fitSURV <- survreg(Surv(years, status2) ~ drug, data = pbc2.id, x = TRUE)
# joint model fit, under the (default) Weibull model
fitJOINT <- jointModel(fitLME, fitSURV, timeVar = "year")

plot(fitJOINT, 3, add.KM = TRUE, col = "red", lwd = 2)

par(mfrow = c(2, 2))
plot(fitJOINT)


[Package JM version 0.2-2 Index]