| PITS-package | PITS: Power of Interrupted Time Series studies |
| build_param_grid | Build a factorial parameter grid for power calculations |
| calculate_power | Estimate statistical power for a single-site ITS design |
| calculate_power_multi | Estimate statistical power for a multi-site ITS design |
| diagnose_params | Diagnostic plots for pre-intervention data |
| estimate_and_calculate | Estimate parameters and calculate power in one step |
| estimate_baseline | Estimate baseline outcome from pre-intervention data |
| estimate_its_params | Estimate all ITS nuisance parameters from pre-intervention data |
| estimate_rho | Estimate AR(1) autocorrelation from pre-intervention data |
| estimate_sigma | Estimate residual standard deviation from pre-intervention data |
| estimate_trend | Estimate pre-intervention trend from pre-intervention data |
| example_cfr_data | Example pre-intervention case fatality rate data |
| export_results | Export PITS results to CSV and plain-text summary |
| fit_its_model | Fit a segmented regression model to an ITS dataset |
| interpret_power | Interpret a power estimate qualitatively |
| PITS | PITS: Power of Interrupted Time Series studies |
| plot_its_example | Plot a simulated ITS example |
| plot_power_curve | Plot power as a function of post-intervention duration |
| plot_power_heatmap | Plot a power heatmap across two parameters |
| power_sweep | Design optimisation sweep: power across a range of n_post values |
| print.pits_power_result | Print method for PITS power results |
| print.pits_sweep_result | Print method for PITS sweep results |
| run_its_power | Full single-site ITS power workflow |
| run_power_grid | Run power calculations across a parameter grid |
| simulate_its_data | Simulate a single ITS dataset |
| simulate_predata | Generate synthetic pre-intervention data |
| summary.pits_power_result | Summary method for PITS power results |
| validate_params | Validate ITS parameter values before simulation |