Plot predicted biomarker distributions

Plots the predicted distribution of the biomarker at prediction_time + horizon returned by predictLongitudinal, one curve per patient, with a dashed line at the patient's point prediction (the most likely value, Y_predict). For an ordinal biomarker, plots each patient's predicted category probabilities as bars instead.

Usage

# S3 method for class 'predictLongitudinal.BJM'
plot(x, subject = NULL, ...)

Arguments

x

A predictLongitudinal.BJM object, i.e. the result of predictLongitudinal() for a single biomarker. For several biomarkers, plot one element of the returned list, e.g. plot(result[["serBilir"]]).

subject

Patients to plot, as ids (the names of x$Y_predict) or positions. NULL (default) plots every patient, or the first six when there are more.

...

Currently unused.

Value

A ggplot object.

Examples

# \donttest{
data(pbc3)
survival_fit_all <- survivalSub(pbc3[!duplicated(pbc3$id), ],
                                Surv(years, status3) ~ age + sex, NULL)
long_sub_fixed <- list("long1" = serBilir ~ year + age + sex + years)
long_sub_random <- list("long1" = ~ year | id)
long_fit_all <- longitudinalSub(list(pbc3[pbc3$status3 == 1, ]),
                                long_sub_fixed, long_sub_random)

data_predict <- pbc3[pbc3$id %in% c(2, 4, 5) & pbc3$year <= 3, ]
data_predict$years <- NA
trans <- survivalTrans(c(1, 3, 5, 7))
pred <- predictLongitudinal(data_predict, long_fit_all, survival_fit_all,
  prediction_time = 3, horizon = 1, time_variable = "year",
  trans$survival_variable_all, trans$survival_trans_function, bio_i = 1)
plot(pred)

# }