if (.Platform$OS.type != "windows" || .Platform$r_arch != "i386") {
# \donttest{
# Run example model if not already loaded
if (!exists("example_jm")) example(example_jm)
# Obtain subject-specific conditional survival probabilities
# for all individuals in the estimation dataset.
ps1 <- posterior_survfit(example_jm, extrapolate = TRUE)
# We then plot the conditional survival probabilities for
# a subset of individuals
plot(ps1, ids = c(7,13,15))
# We can change or add attributes to the plot
plot(ps1, ids = c(7,13,15), limits = "none")
plot(ps1, ids = c(7,13,15), xlab = "Follow up time")
plot(ps1, ids = c(7,13,15), ci_geom_args = list(fill = "red"),
color = "blue", linetype = 2)
plot(ps1, ids = c(7,13,15), facet_scales = "fixed")
# Since the returned plot is also a ggplot object, we can
# modify some of its attributes after it has been returned
plot1 <- plot(ps1, ids = c(7,13,15))
plot1 +
ggplot2::theme(strip.background = ggplot2::element_blank()) +
ggplot2::coord_cartesian(xlim = c(0, 15)) +
ggplot2::labs(title = "Some plotted survival functions")
# We can also combine the plot(s) of the estimated
# subject-specific survival functions, with plot(s)
# of the estimated longitudinal trajectories for the
# same individuals
ps1 <- posterior_survfit(example_jm, ids = c(7,13,15))
pt1 <- posterior_traj(example_jm, , ids = c(7,13,15))
plot_surv <- plot(ps1)
plot_traj <- plot(pt1, vline = TRUE, plot_observed = TRUE)
plot_stack_jm(plot_traj, plot_surv)
# Lastly, let us plot the standardised survival function
# based on all individuals in our estimation dataset
ps2 <- posterior_survfit(example_jm, standardise = TRUE, times = 0,
control = list(epoints = 20))
plot(ps2)
# }
}
if (.Platform$OS.type != "windows" || .Platform$r_arch != "i386") {
# \donttest{
if (!exists("example_jm")) example(example_jm)
ps1 <- posterior_survfit(example_jm, ids = c(7,13,15))
pt1 <- posterior_traj(example_jm, ids = c(7,13,15), extrapolate = TRUE)
plot_surv <- plot(ps1)
plot_traj <- plot(pt1, vline = TRUE, plot_observed = TRUE)
plot_stack_jm(plot_traj, plot_surv)
# }
}
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