fit_model               Fit a model for a single simulated dataset
mp_assumptions          Create modeling assumptions for
                        simulation-based power
mp_backend_lme4         Build an lme4 backend for MixPower scenarios
mp_backend_lme4_binomial
                        Build an lme4 backend for binomial GLMM
                        scenarios
mp_backend_lme4_nb      Build an lme4 backend for Negative Binomial
                        GLMM scenarios
mp_backend_lme4_poisson
                        Build an lme4 backend for Poisson GLMM
                        scenarios
mp_bundle_results       Bundle results with manifest and optional
                        labels
mp_design               Create a study design specification
mp_manifest             Reproducibility manifest for power analyses
mp_power                Simulation-based power estimation
                        (engine-agnostic core)
mp_power_curve          Power curve for a single design/assumption
                        parameter
mp_power_curve_parallel
                        Parallel power curve evaluation
mp_report_table         Publication-ready summary table for power
                        results
mp_scenario             Create a power-analysis scenario
mp_scenario_lme4        Create a fully specified MixPower scenario with
                        the lme4 backend
mp_scenario_lme4_binomial
                        Create a fully specified MixPower scenario with
                        the binomial lme4 backend
mp_scenario_lme4_nb     Create a fully specified MixPower scenario with
                        the NB lme4 backend
mp_scenario_lme4_poisson
                        Create a fully specified MixPower scenario with
                        the Poisson lme4 backend
mp_sensitivity          Run power sensitivity analysis over a parameter
                        grid
mp_solve_sample_size    Solve for minimum sample size achieving target
                        power
mp_write_results        Write results or bundle to CSV or JSON
plot.mp_power_curve     Plot a power curve
plot.mp_sensitivity     Plot a one-dimensional sensitivity curve
plot_power              Plot power results
run_parallel            Placeholder for parallel execution
simulate_glmm_binomial_data
                        Simulate binary outcome data for a GLMM with
                        random intercepts
simulate_glmm_nb_data   Simulate count outcome data for a Negative
                        Binomial GLMM
simulate_glmm_poisson_data
                        Simulate count outcome data for a Poisson GLMM
                        with random intercepts
simulate_power          Run a simple simulation-based power study
summarize_simulations   Summarize simulation outputs
test_effect             Extract a test statistic for a model term
