Calibration Plot

Creates calibration curves for assessing prediction model performance. Shows predicted probabilities vs. observed frequencies with an ideal reference line, LOESS smooth, and optional histogram of predictions.

Usage

CalibrationPlot(
  data,
  predicted,
  observed,
  n_bins = 10,
  method = c("loess", "bins"),
  add_histogram = TRUE,
  add_ci = TRUE,
  ideal_color = "grey50",
  smooth_color = "red2",
  smooth_width = 1,
  pt_size = 3,
  split_by = NULL,
  split_by_sep = "_",
  theme = "theme_ggforge_grid",
  theme_args = list(),
  palette = "forge",
  palcolor = NULL,
  alpha = 1,
  legend.position = "none",
  legend.direction = "vertical",
  title = NULL,
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  seed = 8525,
  combine = TRUE,
  nrow = NULL,
  ncol = NULL,
  byrow = TRUE,
  axes = NULL,
  axis_titles = NULL,
  guides = NULL,
  design = NULL,
  ...
)

Arguments

data: A data frame containing the data to plot
predicted: Column of predicted probabilities.
observed: Column of binary observed outcomes (0/1).
n_bins: Number of calibration bins (default 10).
method: Smoothing method: "loess" or "bins".
add_histogram: Whether to add a rug/histogram of predicted values.
add_ci: Whether to show confidence intervals.
ideal_color: Color for the ideal (diagonal) line.
smooth_color: Color for the calibration curve.
smooth_width: Line width for calibration curve.
pt_size: Point size for binned calibration.
split_by: Column name(s) to split data into multiple plots
split_by_sep: Separator when concatenating multiple split_by columns
theme: Theme name (string) or theme function
theme_args: List of arguments passed to theme function
palette: Color palette name
palcolor: Custom colors for palette
alpha: Transparency level (0-1)
legend.position: Legend position: "none", "left", "right", "bottom", "top"
legend.direction: Legend direction: "horizontal" or "vertical"
title: Plot title
subtitle: Plot subtitle
xlab: X-axis label
ylab: Y-axis label
seed: Random seed for reproducibility
combine: Whether to combine split plots into one
nrow: Number of rows when combining plots
ncol: Number of columns when combining plots
byrow: Fill combined plots by row
axes: How to handle axes in combined plots ("keep", "collect", "collect_x", "collect_y")
axis_titles: How to handle axis titles in combined plots
guides: How to handle guides in combined plots ("collect", "keep", "auto")
design: Custom layout design for combined plots
...: Additional arguments passed to atomic plotting functions.

Value

A ggplot object or combined plots

Examples

# \donttest{
set.seed(42)
n <- 200
x <- rnorm(n)
prob <- 1 / (1 + exp(-x))
outcome <- rbinom(n, 1, prob)
predicted <- 1 / (1 + exp(-(x + rnorm(n, 0, 0.3))))
data <- data.frame(predicted = predicted, observed = outcome)
CalibrationPlot(data, predicted = "predicted", observed = "observed")

# }

Usage

Arguments

Value

See also

Examples