Table 5.
Example | Predicted PPV and NPV obtained using… | Statistical framework | Summary O/E (95% CI) | (95% CI) | 95% prediction interval for O/E in a new population | Probability 0.9 < O/E < 1.1 in a new population |
---|---|---|---|---|---|---|
Temperature data | Option A | Bayesian | 1.02 (0.93 to 1.11) | 0.10 (0.01 to 0.23) | 0.78 to 1.31 | 0.67 |
Option A | Frequentist | 1.02 (0.95 to 1.10) | 0.08 | 0.85 to 1.24 | — | |
PTH data 1–2 h | Option B | Bayesian | 1.02 (0.73 to 1.38) | 0.14 (0.01 to 0.45) | 0.56 to 1.74 | 0.40 |
Option B | Frequentist | 1.01 (0.79 to 1.29) | 0 | 0.68 to 1.50 | — |
All frequentist analyses used method of moments to estimate the model.
All Bayesian analyses used a prior N(0, 1 000 000) for the mean ln(O/E) and a prior uniform(0, 0.25) for τ, with a 10 000 burn‐in followed by 100 000 samples for posterior inferences.
O/E, observed/expected; PPV, positive predictive value; NPV, negative predictive value.