add_integration         Add numerical integration points
calculate_dic           Calculate DIC for model comparison
calculate_loo           Calculate LOO-CV for an mlumr_fit
calculate_waic          Calculate WAIC for an mlumr_fit
check_integration       Check integration point adequacy
combine_data            Combine IPD and AgD for unanchored comparison
compare_models          Compare fitted ML-UMR models
conditional_effects     Conditional treatment effects
conditional_predict     Conditional predictions
dbern                   Bernoulli PMF
default_priors          Default priors used by 'mlumr()'
distr                   Specify a marginal distribution
marginal_effects        Marginal treatment effects
mlumr                   Fit ML-UMR Model
mlumr_engine            Get or Set the Stan Engine
naive                   Naive unadjusted indirect comparison
pbern                   Bernoulli CDF
predict.mlumr_fit       Predictions from ML-UMR model
prior_cauchy            Specify a Cauchy prior
prior_exponential       Specify an exponential prior
prior_normal            Specify a normal prior
prior_sensitivity       Prior sensitivity analysis for an ML-UMR fit
prior_student_t         Specify a Student-t prior
prior_summary           Summary of priors used by a fitted ML-UMR model
qbern                   Bernoulli quantile function
set_agd                 Set up aggregate data (AgD)
set_ipd                 Set up individual patient data (IPD)
stc                     Simulated treatment comparison via
                        G-computation
unnest_integration      Expand integration points into a long-format
                        data frame
