GammaDist               The Gamma distribution, parameterized by mean
                        and standard deviation
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
caries_agd              Dental caries: simulated comparator aggregate
                        data (count)
caries_ipd              Dental caries: simulated index IPD (count)
check_diagnostics       Check the sampler diagnostics of a fit
check_identification    Can the aggregate data identify the comparator
                        coefficients?
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
geom_km                 Observed Kaplan-Meier layer for survival
                        overlays
logitNormal             The logit-Normal distribution
make_knots              Choose M-spline knots for a flexible-baseline
                        survival model
marginal_effects        Marginal treatment effects
mlumr                   Fit ML-UMR Model
mlumr_engine            Get or set the Stan engine
mlumr_forest            Forest plot of a small set of estimates
naive                   Naive unadjusted indirect comparison
ndmm_agd                Newly diagnosed multiple myeloma: comparator
                        pseudo-IPD (survival)
ndmm_agd_covs           Newly diagnosed multiple myeloma: comparator
                        covariate summaries (survival)
ndmm_ipd                Newly diagnosed multiple myeloma: index
                        individual patient data (survival)
pbern                   Bernoulli CDF
plot.mlumr_conditional_effects
                        Plot covariate-conditional treatment effects
plot.mlumr_marginal_effects
                        Forest plot of population-standardized marginal
                        effects
plot.mlumr_prediction   Plot absolute predictions from a fitted ML-UMR
                        model
plot_prior_posterior    Prior-versus-posterior overlay
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
psoriasis_agd           Plaque psoriasis: comparator aggregate data
                        (binary)
psoriasis_ipd           Plaque psoriasis: index individual patient data
                        (binary)
qbern                   Bernoulli quantile function
set_agd                 Set up aggregate data (AgD)
set_agd_surv            Set up aggregate survival data (reconstructed
                        pseudo-IPD)
set_ipd                 Set up individual patient data (IPD)
shoulder_agd            Shoulder pain: simulated comparator aggregate
                        data (continuous)
shoulder_ipd            Shoulder pain: simulated index IPD (continuous)
stc                     Simulated treatment comparison via
                        G-computation
unnest_integration      Expand integration points into a long-format
                        data frame
