AIC.pvEBayes |
Obtain Akaike Information Criterion (AIC) for a pvEBayes object |
BIC.pvEBayes |
Obtain Bayesian Information Criterion (BIC) for a pvEBayes object |
estimate_null_expected_count |
Estimate expected null baseline count based on reference row and column |
extract_all_fitted_models |
Extract all fitted models from a tuned pvEBayes Object |
eyeplot_pvEBayes |
Generate an eyeplot showing the distribution of posterior draws for selected drugs and adverse events |
gbca2025 |
FDA GBCA dataset with 1328 adverse events |
gbca2025_69 |
FDA GBCA dataset with 69 adverse events |
generate_contin_table |
Generate random contingency tables based on a reference table embedded signals,and possibly with zero inflation |
heatmap_pvEBayes |
Generate a heatmap plot visualizing posterior probabilities for selected drugs and adverse events |
logLik.pvEBayes |
Extract log marginal likelihood for a pvEBayes object |
plot.pvEBayes |
Plotting method for a pvEBayes object |
posterior_draws |
Generate posterior draws for each AE-drug combination |
print.pvEBayes |
Print method for a pvEBayes object |
pvEBayes |
Fit a general-gamma, GPS, K-gamma, KM or efron model for a contingency table. |
pvEBayes_tune |
Select hyperparameter and obtain the optimal general-gamma or efron model based on AIC and BIC |
statin2025 |
FDA statin dataset with 5119 adverse events |
statin2025_44 |
FDA statin dataset with 44 adverse events |
statin42 |
FDA statin dataset with 42 adverse events |
summary.pvEBayes |
Summary method for a pvEBayes object |