Simulation-Based Power Analysis for Mixed-Effects Models

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Documentation for package ‘mixpower’ version 0.1.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

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