API Reference

Complete reference for the MCPower class and its public API.

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Quick Reference

Method / Class	Description
MCPower(formula)	Create a power analysis model from an R-style formula
find_power()	Estimate statistical power at a given sample size
find_sample_size()	Find the minimum sample size for target power
set_effects()	Set standardized effect sizes (beta weights)
set_variable_type()	Declare binary, factor, or non-normal variables
set_correlations()	Specify predictor correlations
set_alpha()	Set the significance level
set_power()	Set the target power level (for sample size search)
set_seed()	Set random seed for reproducibility
set_simulations()	Set number of Monte Carlo simulations
set_parallel()	Configure parallel execution
upload_data()	Upload empirical data for realistic simulation
set_factor_levels()	Define named factor levels
set_cluster()	Configure clustering for mixed-effects models
set_scenario_configs()	Customize scenario analysis parameters
set_max_failed_simulations()	Set convergence failure tolerance
Correction methods	Multiple testing correction options
Progress reporting	Progress callbacks and built-in reporters
Return values	Result dictionary structures

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Pages

• MCPower() Constructor
  • MCPower
  • Formula Syntax
  • Examples
  • Defaults After Construction
  • See Also
• Power Analysis
  • find_power()
  • find_sample_size()
• Configuration
  • set_effects()
  • set_variable_type()
  • set_correlations()
  • set_alpha()
  • set_power()
  • set_seed()
  • set_simulations()
  • set_parallel()
• Data & Clustering
  • upload_data()
  • set_factor_levels()
  • set_cluster()
• Scenario Analysis
  • set_scenario_configs()
  • set_max_failed_simulations()
• Correction Methods
  • Available Corrections
  • How Corrections Interact with Tests
  • Examples
  • Technical Details
  • References
  • See Also
• Progress Reporting
  • Resolution Logic
  • Built-in Reporters
  • Custom Callbacks
  • Disabling Progress
  • Total Simulation Count
  • See Also
• Return Values
  • Enabling Return Values
  • Result Structure: find_power()
  • Result Structure: find_sample_size()
  • Examples
  • Notes
  • See Also