as_tibble.mp_power      Coerce mixpower results to a tibble
autoplot.mp_sensitivity
                        ggplot2 diagnostic plot for sensitivity or
                        power curve
effect_size             Effect-size converters for eliciting
                        assumptions
fit_model               Fit a model for a single simulated dataset
mixpower-package        Simulation-Based Power Analysis for
                        Mixed-Effects Models
mp_assumptions          Create modeling assumptions for
                        simulation-based power
mp_backend              MixPower backend contract
mp_backend_glmmtmb      Build a glmmTMB backend for Gaussian LMM
                        scenarios
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_calibrate            Check the Type I error calibration of a
                        scenario's test
mp_compare_models       Compare analysis models on the same simulated
                        data
mp_design               Create a study design specification
mp_extend               Scale a fitted-model scenario's sample size up
                        or down
mp_from_fit             Build a power scenario from a fitted lme4 model
mp_grid_sample_size     Create a grid of values for sample-size search
mp_manifest             Reproducibility manifest for power analyses
mp_methods_text         Generate a methods paragraph for a power
                        analysis
mp_missing              Add a missing-data / dropout mechanism to a
                        scenario
mp_power                Simulation-based power estimation
                        (engine-agnostic core)
mp_power_checkpoint     Resumable, checkpointed power simulation
mp_power_curve          Power curve for a single design/assumption
                        parameter
mp_power_curve_parallel
                        Parallel power curve evaluation
mp_quick_power          Quick power run for a single LMM design
mp_recommend_method     Recommend an inference method for a scenario
mp_report_table         Publication-ready summary table for power
                        results
mp_safeguard_effect     Safeguard (confidence-bound) effect size from a
                        fitted model
mp_scenario             Create a power-analysis scenario
mp_scenario_glmmtmb_lmm
                        Gaussian LMM scenario using glmmTMB
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_sensitivity_parallel
                        Parallel sensitivity analysis over a parameter
                        grid
mp_sesoi                Set a smallest effect size of interest (SESOI)
                        on a scenario
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           Plot the p-value distribution of a power
                        analysis
plot.mp_power_curve     Plot a power curve
plot.mp_sensitivity     Plot a sensitivity analysis
plot_power              Plot power results
run_parallel            Placeholder for parallel execution
simulate_glmm_binomial_data
                        Simulate binary outcome data for a GLMM with
                        random effects
simulate_glmm_nb_data   Simulate count outcome data for a Negative
                        Binomial GLMM with random effects
simulate_glmm_poisson_data
                        Simulate count outcome data for a Poisson GLMM
                        with random effects
simulate_power          Run a simple simulation-based power study
summarize_simulations   Summarize simulation outputs
test_effect             Extract a test statistic for a model term
validate_mp_backend     Validate a MixPower backend
