Observed Kaplan-Meier layer for survival overlays

Returns ggplot2 layers drawing the observed Kaplan-Meier step curves (the index IPD and the reconstructed comparator pseudo-IPD) of a survival mlumr_data, colored by treatment so they line up with a survival prediction plot. The mlumr analogue of multinma's geom_km(), so a predicted-versus-observed figure is just plot(predict(fit, type = "survival")) + geom_km(data).

Usage

geom_km(
  data,
  treatments = NULL,
  population = NULL,
  marks = TRUE,
  linewidth = 0.4,
  ...
)

Arguments

data

An mlumr_data survival object from combine_data().

treatments

Optional character vector of treatment labels to draw. By default both observed arms are drawn. This cannot separate the arms when both carry the same label; use population there. A label that names no observed arm is refused rather than drawn as nothing.

population

Optional cohort to draw, "Index" and/or "Comparator". Selects the arm itself rather than its display name, so population = "Comparator" overlays only the comparator KM on a comparator-population prediction whatever the treatments are called. Only the selected cohorts are examined: a left- or interval-censored observation in a cohort that is not drawn does not stop the plot, and one in a cohort that is drawn refuses it.

marks

Logical; draw censoring marks (default TRUE).

linewidth

Step line width (default 0.4).

...

Passed to ggplot2::geom_step().

Value

A list of ggplot2 layers (a step layer, plus a censoring-mark layer when marks = TRUE) to add to a plot with +. The layers carry the population each observed arm was measured in, so on a plot faceted by population each curve appears only in its own panel. A plot standardized to a newdata target therefore shows no observed curve, which is correct: no arm was observed in that population.

See also

plot.mlumr_prediction()

Examples

if (FALSE) { # \dontrun{
plot(predict(fit, type = "survival")) + geom_km(dat)
plot(predict(fit, type = "survival")) + geom_km(dat, population = "Comparator")
} # }