Prints a formatted summary of Monte Carlo simulation results.
Arguments
- mc_results
Output from
run_hurdle_monte_carlo.- digits
Number of digits to display. Default is 3.
Examples
# \donttest{
# Tiny run for illustration (use n_sim >= 200 for a real calibration study)
mc_results <- run_hurdle_monte_carlo(n_sim = 5, n_subjects = 30, seed = 123,
verbose = FALSE)
print_mc_summary(mc_results)
#>
#> Monte Carlo Simulation Summary
#> ==============================
#>
#> Simulations: 5 attempted, 5 converged (100.0%)
#>
#> Parameter True Mean_Est Bias Rel_Bias% Emp_SE Mean_SE SE_Ratio
#> beta0 -2.000 -2.287 -0.287 -14.4 0.305 0.508 1.67
#> beta1 1.000 1.303 0.303 30.3 0.345 0.794 2.30
#> log_q0 2.303 2.316 0.014 0.6 0.073 0.106 1.46
#> k 2.000 NA NA NA NA NA NA
#> alpha 0.500 NA NA NA NA NA NA
#> logsigma_a 0.000 -0.616 -0.616 NA 1.361 1.420 1.04
#> logsigma_b -0.693 -0.651 0.043 6.1 0.092 0.138 1.50
#> logsigma_e -1.204 -1.269 -0.065 -5.4 0.093 0.059 0.64
#> rho_ab_raw 0.310 1.420 1.111 358.9 3.000 834.738 278.21
#> Coverage_95% N
#> 100 5
#> 100 5
#> 100 5
#> NA 0
#> NA 0
#> 100 5
#> 100 5
#> 60 5
#> 100 5
#>
#> Interpretation:
#> - SE Ratio close to 1.0 indicates well-calibrated SEs
#> - Coverage close to 95% indicates valid confidence intervals
#> - Relative bias < 5% is generally acceptable
# }