Plots calibration curves estimated using calib_msm.

Plots calibration curves for the transition probabilities of a multistate model estimated using BLR-IPCW and pseudo-value approaches.

Usage

# S3 method for class 'calib_msm'
plot(
  x,
  ...,
  combine = TRUE,
  ncol = NULL,
  nrow = NULL,
  size_line = 0.5,
  size_text = 12,
  marg_density = TRUE,
  marg_density_size = 5,
  marg_density_type = "density",
  marg_rug = FALSE,
  marg_rug_transparency = 0.1,
  titles_include = TRUE,
  titles = NULL,
  axis_titles_x = NULL,
  axis_titles_text_x = "Predicted risk",
  axis_titles_y = NULL,
  axis_titles_text_y = "Predicted-observed risk",
  legend_include = TRUE,
  legend_seperate = FALSE,
  legend_title = NULL,
  legend_position = "bottom"
)

Arguments

x: Object of class 'calib_msm' generated from calib_msm.
...: Other
combine: Whether to combine into one plot using ggarrange, or return as a list of individual plots
ncol: Number of columns for combined calibration plot
nrow: Number of rows for combined calibration plot
size_line: Size of line plots
size_text: Size of text in plot
marg_density: Whether to produce marginal density plots TRUE/FALSE
marg_density_size: Size of the main plot relative to the density plots (see ggMarginal)
marg_density_type: What type of marginal plot to show (see ggMarginal)
marg_rug: Whether to produce marginal rug plots TRUE/FALSE
marg_rug_transparency: Degree of transparency for the density rug plot along each axis
titles_include: Whether to include titles for each individual calibration plots
titles: Vector of titles for the calibration plots. Defaults to "State k" for each plot.
axis_titles_x: Position of plots for which to include title on x-axis
axis_titles_text_x: x-axis title
axis_titles_y: Position of plots for which to include title on y-axis
axis_titles_text_y: y-axis title
legend_include: Whether to produce a legend
legend_seperate: = Whether to include legend in plot (FALSE) or as a seperate object (TRUE)
legend_title: Title of legend
legend_position: Position of legend

Value

If combine = TRUE, returns an object of classes gg, ggplot, and ggarrange, as all ggplots have been combined into one object. If combine = FALSE, returns an object of class list, each element containing an object of class gg and ggplot.

Examples

# Estimate and plot BLR-IPCW calibration curves for the predicted transition
# probabilities at time t = 1826, when predictions were made at time
# s = 0 in state j = 1. These predicted transition probabilities are stored in tps0.

# Extract the predicted transition probabilities out of state j = 1
tp_pred <- dplyr::select(dplyr::filter(tps0, j == 1), any_of(paste("pstate", 1:6, sep = "")))

# Now estimate the observed event probabilities for each possible transition.
dat_calib <-
calib_msm(data_ms = msebmtcal,
 data_raw = ebmtcal,
 j=1,
 s=0,
 t = 1826,
 tp_pred = tp_pred,
 w_covs = c("year", "agecl", "proph", "match"))

 # These are then plotted
 plot(dat_calib, combine = TRUE, nrow = 2, ncol = 3)
#> TableGrob (2 x 3) "arrange": 6 grobs
#>   z     cells    name                grob
#> 1 1 (1-1,1-1) arrange ggExtraPlot[layout]
#> 2 2 (1-1,2-2) arrange ggExtraPlot[layout]
#> 3 3 (1-1,3-3) arrange ggExtraPlot[layout]
#> 4 4 (2-2,1-1) arrange ggExtraPlot[layout]
#> 5 5 (2-2,2-2) arrange ggExtraPlot[layout]
#> 6 6 (2-2,3-3) arrange ggExtraPlot[layout]