Summarise a study design optimization — summary.movedesign

Print a structured summary of a movedesign_optimized object produced by md_optimize(). The summary reports the study design, replication settings, estimation performance for each target metric, and a convergence assessment.

This method runs automatically when calling summary(output) on a movedesign_optimized object.

Usage

# S3 method for class 'movedesign_optimized'
summary(
  object,
  verbose = FALSE,
  error_threshold = NULL,
  m = NULL,
  ci = 0.95,
  tol = 0.05,
  n_converge = 9,
  plot = TRUE,
  pal = c("#007d80", "#A12C3B"),
  ...
)

Arguments

object: A movedesign_optimized object returned by md_replicate() or md_stack().
verbose: Logical. If TRUE, run md_check() and print the full convergence diagnostics. This can also display a convergence plot when plot = TRUE. If FALSE (default), only the convergence status is printed.
error_threshold: Numeric. Upper limit of the relative error in estimation (e.g., 0.05 for 5%) deemed acceptable by the user.
m: Numeric (Optional). If provided, restricts the results to a specific population sample size (m). Defaults to NULL, which checks up to the maximum population sample size.
ci: Confidence level for the intervals. Applied to both the narrow confidence bars and wide prediction bands. Must be between 0 and 1. Default: 0.95 (95%).
tol: Numeric. The tolerance threshold for absolute change in the cumulative mean to declare convergence. Defaults to 0.05.
n_converge: Integer. Number of consecutive steps within tolerance required to confirm convergence.
plot: Logical. If TRUE (default), generates a plot of stepwise changes in the cumulative mean, highlighting when convergence is achieved.
pal: Character vector of color(s) of the plot, such as c("#007d80", "#A12C3B")) (default).
...: Additional arguments