Table 2. Markov Chain Monte Carlo simulations.
| Observed Data (Binomial) | Prior (Beta) |
Simulation Results | |||||
|---|---|---|---|---|---|---|---|
| Probabilities | Events | Total | Events | No Events | Mean | Median | Credible Interval |
| GSTP1 High Risk (P1) | 45 | 88 | 178 | 114 | 0.587 | 0.586 | 0.538–0.634 |
| Grade 3/4 Nausea (P2) | 4 | 43 | 33 | 191 | 0.139 | 0.138 | 0.100–0.181 |
| Second Cycle Administration (P3) | 86 | 88 | 160 | 12 | 0.947 | 0.948 | 0.917–0.970 |
| Third Cycle Administration (P4) | 64 | 86 | 120 | 40 | 0.748 | 0.748 | 0.692–0.800 |
Markov chain Monte Carlo simulations performed by Metropolis-Hastings algorithm, describing binomial, beta distributions, as well as the resulting proportions for each simulation and their respective credible intervals.
Notes: MCMC iterations = 12,500; Burn-in = 2,500; MCMC sample size = 10,000