plot.pmcalibration: Plot a calibration curve

In pmcalibration: Calibration Curves for Clinical Prediction Models

Plot a calibration curve

Description

Plot a pmcalibration object. For binary outcomes, also plot the distribution of predicted risks by outcome. Alternatively you can use get_curve() to get the data required to plot the calibration curve.

Usage

## S3 method for class 'pmcalibration'
plot(
  x,
  conf_level = 0.95,
  riskdist = TRUE,
  linecol = "black",
  fillcol = "grey",
  ideallty = 2,
  idealcol = "red",
  ...
)

Arguments

x	a pmcalibration calibration curve
conf_level	width of the confidence interval (0.95 gives 95% CI). Ignored if call to pmcalibration didn't request confidence intervals
riskdist	add risk distribution plot under calibration curve (TRUE) or not (FALSE)
linecol	color of the calibration curve line
fillcol	color of the confidence interval
ideallty	line type of the ideal unit slope line
idealcol	color of the ideal unit slope line
...	other args for plot() (currently only lims and labs can be specified)

Value

No return value, called for side effects

Examples

library(pmcalibration)
# simulate some data with a binary outcome
n <- 500
dat <- sim_dat(N = n, a1 = .5, a3 = .2)
head(dat)
# predictions
p <- with(dat, invlogit(.5 + x1 + x2 + x1*x2*.1))

# fit calibration curve
cal <- pmcalibration(y = dat$y, p = p, smooth = "gam", k = 20, ci = "pw", plot = FALSE)

plot(cal, xlab = "Predicted Risk of Outcome") # customize plot

pmcalibration documentation built on April 4, 2025, 2:23 a.m.