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joineRML (version 0.4.6)

plot.dynLong: Plot a dynLong object

Description

Plots the conditional longitudinal expectations for a new subject calculated using the dynLong function.

Usage

# S3 method for dynLong
plot(x, main = NULL, xlab = NULL, ylab = NULL, grid = TRUE, estimator, ...)

Value

A dynamic prediction plot.

Arguments

x

an object of class dynLong calculated by the dynLong function.

main

an overall title for the plot: see title.

xlab

a title for the x [time] axis: see title.

ylab

a character vector of the titles for the K longitudinal outcomes y-axes: see title.

grid

adds a rectangular grid to an existing plot: see grid.

estimator

a character string that can take values mean or median to specify what prediction statistic is plotted from an objecting inheritting of class dynSurv. Default is estimator='median'. This argument is ignored for non-simulated dynSurv objects, i.e. those of type='first-order', as in that case a mode-based prediction is plotted.

...

additional plotting arguments; currently limited to lwd and cex. See par for details.

Author

Graeme L. Hickey (graemeleehickey@gmail.com)

References

Rizopoulos D. Dynamic predictions and prospective accuracy in joint models for longitudinal and time-to-event data. Biometrics. 2011; 67: 819–829.

See Also

dynLong

Examples

Run this code
if (FALSE) {
# Fit a joint model with bivariate longitudinal outcomes

data(heart.valve)
hvd <- heart.valve[!is.na(heart.valve$log.grad) & !is.na(heart.valve$log.lvmi), ]

fit2 <- mjoint(
    formLongFixed = list("grad" = log.grad ~ time + sex + hs,
                         "lvmi" = log.lvmi ~ time + sex),
    formLongRandom = list("grad" = ~ 1 | num,
                          "lvmi" = ~ time | num),
    formSurv = Surv(fuyrs, status) ~ age,
    data = list(hvd, hvd),
    inits = list("gamma" = c(0.11, 1.51, 0.80)),
    timeVar = "time",
    verbose = TRUE)

hvd2 <- droplevels(hvd[hvd$num == 1, ])
out <- dynLong(fit2, hvd2)
plot(out, main = "Patient 1")
}

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