# API Reference Complete reference for the `MCPower` class and its public API. --- ## Quick Reference | Method / Class | Description | |---|---| | [`MCPower(formula)`](constructor.md) | Create a power analysis model from an R-style formula | | {ref}`find_power() ` | Estimate statistical power at a given sample size | | {ref}`find_sample_size() ` | Find the minimum sample size for target power | | {ref}`set_effects() ` | Set standardized effect sizes (beta weights) | | {ref}`set_variable_type() ` | Declare binary, factor, or non-normal variables | | {ref}`set_correlations() ` | Specify predictor correlations | | {ref}`set_alpha() ` | Set the significance level | | {ref}`set_power() ` | Set the target power level (for sample size search) | | {ref}`set_seed() ` | Set random seed for reproducibility | | {ref}`set_simulations() ` | Set number of Monte Carlo simulations | | {ref}`set_parallel() ` | Configure parallel execution | | {ref}`upload_data() ` | Upload empirical data for realistic simulation | | {ref}`set_factor_levels() ` | Define named factor levels | | {ref}`set_cluster() ` | Configure clustering for mixed-effects models | | {ref}`set_scenario_configs() ` | Customize scenario analysis parameters | | {ref}`set_max_failed_simulations() ` | Set convergence failure tolerance | | [Correction methods](corrections.md) | Multiple testing correction options | | [Progress reporting](progress.md) | Progress callbacks and built-in reporters | | [Return values](return-values.md) | Result dictionary structures | --- ## Pages ```{toctree} :maxdepth: 2 constructor power-analysis configuration data scenarios corrections progress return-values ```