plot | R Documentation |
Produces a variety of plots for fitted joint models.
## 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, return = FALSE)
x |
an object inheriting from class |
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 |
survTimes |
a vector of survival times for which the survival, cumulative hazard or
log cumulative hazard will be computed. Default is |
main |
a character string specifying the title in the plot. |
ask |
logical; if |
... |
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 |
add.qqline |
logical; if |
add.KM |
logical; if |
cex.caption |
magnification of captions. |
return |
logical; if |
The plots of the baseline hazard and the cumulative baseline hazard are only produced when the joint model has
been fitted using method = "Cox-PH-GH"
.
Dimitris Rizopoulos d.rizopoulos@erasmusmc.nl
Rizopoulos, D. (2012) Joint Models for Longitudinal and Time-to-Event Data: with Applications in R. Boca Raton: Chapman and Hall/CRC.
Rizopoulos, D. (2010) JM: An R package for the joint modelling of longitudinal and time-to-event data. Journal of Statistical Software 35 (9), 1–33. doi: 10.18637/jss.v035.i09
jointModel
## Not run: # 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) ## End(Not run)
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