A B C D E F G H I L M N P Q R S T U W misc
| multinma-package | multinma: A Package for Network Meta-Analysis of Individual and Aggregate Data in Stan | 
| adapt_delta | Target average acceptance probability | 
| add_integration | Add numerical integration points to aggregate data | 
| add_integration.data.frame | Add numerical integration points to aggregate data | 
| add_integration.default | Add numerical integration points to aggregate data | 
| add_integration.nma_data | Add numerical integration points to aggregate data | 
| as.array.nma_dic | Methods for 'nma_dic' objects | 
| as.array.nma_rank_probs | Methods for 'nma_summary' objects | 
| as.array.nma_summary | Methods for 'nma_summary' objects | 
| as.array.stan_nma | Convert samples into arrays, matrices, or data frames | 
| as.data.frame.nma_dic | Methods for 'nma_dic' objects | 
| as.data.frame.nma_summary | Methods for 'nma_summary' objects | 
| as.data.frame.nodesplit_summary | Methods for 'nodesplit_summary' objects | 
| as.data.frame.stan_nma | Convert samples into arrays, matrices, or data frames | 
| as.igraph.nma_data | Convert networks to graph objects | 
| as.matrix.nma_dic | Methods for 'nma_dic' objects | 
| as.matrix.nma_rank_probs | Methods for 'nma_summary' objects | 
| as.matrix.nma_summary | Methods for 'nma_summary' objects | 
| as.matrix.stan_nma | Convert samples into arrays, matrices, or data frames | 
| as.stanfit | as.stanfit | 
| as.stanfit.default | as.stanfit | 
| as.stanfit.stan_nma | as.stanfit | 
| as.tibble.nma_dic | Methods for 'nma_dic' objects | 
| as.tibble.nma_summary | Methods for 'nma_summary' objects | 
| as.tibble.nodesplit_summary | Methods for 'nodesplit_summary' objects | 
| as.tibble.stan_nma | Convert samples into arrays, matrices, or data frames | 
| as_tbl_graph.nma_data | Convert networks to graph objects | 
| as_tibble.nma_dic | Methods for 'nma_dic' objects | 
| as_tibble.nma_summary | Methods for 'nma_summary' objects | 
| as_tibble.nodesplit_summary | Methods for 'nodesplit_summary' objects | 
| as_tibble.stan_nma | Convert samples into arrays, matrices, or data frames | 
| atrial_fibrillation | Stroke prevention in atrial fibrillation patients | 
| bcg_vaccine | BCG vaccination | 
| blocker | Beta blockers to prevent mortality after MI | 
| cauchy | Prior distributions | 
| combine_network | Combine multiple data sources into one network | 
| dbern | The Bernoulli Distribution | 
| dgamma | The Gamma distribution | 
| dgent | Generalised Student's t distribution (with location and scale) | 
| diabetes | Incidence of diabetes in trials of antihypertensive drugs | 
| dic | Deviance Information Criterion (DIC) | 
| dietary_fat | Reduced dietary fat to prevent mortality | 
| distr | Specify a general marginal distribution | 
| dlogitnorm | The logit Normal distribution | 
| dlogt | Log Student's t distribution | 
| dmspline | Distribution functions for M-spline baseline hazards | 
| example_ndmm | Example newly-diagnosed multiple myeloma | 
| example_pso_mlnmr | Example plaque psoriasis ML-NMR | 
| example_smk_fe | Example smoking FE NMA | 
| example_smk_nodesplit | Example smoking node-splitting | 
| example_smk_re | Example smoking RE NMA | 
| example_smk_ume | Example smoking UME NMA | 
| exponential | Prior distributions | 
| flat | Prior distributions | 
| geom_km | Kaplan-Meier curves of survival data | 
| get_nodesplits | Direct and indirect evidence | 
| half_cauchy | Prior distributions | 
| half_normal | Prior distributions | 
| half_student_t | Prior distributions | 
| has_direct | Direct and indirect evidence | 
| has_indirect | Direct and indirect evidence | 
| Hmspline | Distribution functions for M-spline baseline hazards | 
| hmspline | Distribution functions for M-spline baseline hazards | 
| hta_psoriasis | HTA Plaque Psoriasis | 
| inv_softmax | Softmax transform | 
| is_network_connected | Check network connectedness | 
| log_normal | Prior distributions | 
| log_student_t | Prior distributions | 
| loo | Model comparison using the 'loo' package | 
| loo.stan_nma | Model comparison using the 'loo' package | 
| make_knots | Knot locations for M-spline baseline hazard models | 
| marginal_effects | Marginal treatment effects | 
| mcmc_array | Working with 3D MCMC arrays | 
| mcmc_array-class | Working with 3D MCMC arrays | 
| mlnmr_data | The nma_data class | 
| mlnmr_data-class | The nma_data class | 
| multi | Multinomial outcome data | 
| multinma | multinma: A Package for Network Meta-Analysis of Individual and Aggregate Data in Stan | 
| names.mcmc_array | Working with 3D MCMC arrays | 
| names<-.mcmc_array | Working with 3D MCMC arrays | 
| ndmm_agd | Newly diagnosed multiple myeloma | 
| ndmm_agd_covs | Newly diagnosed multiple myeloma | 
| ndmm_ipd | Newly diagnosed multiple myeloma | 
| nma | Network meta-analysis models | 
| nma_data | The nma_data class | 
| nma_data-class | The nma_data class | 
| nma_dic | The nma_dic class | 
| nma_dic-class | The nma_dic class | 
| nma_nodesplit | The nma_nodesplit class | 
| nma_nodesplit-class | The nma_nodesplit class | 
| nma_nodesplit_df | The nma_nodesplit class | 
| nma_nodesplit_df-class | The nma_nodesplit class | 
| nma_prior | The nma_prior class | 
| nma_prior-class | The nma_prior class | 
| nma_rank_probs | The 'nma_summary' class | 
| nma_summary | The 'nma_summary' class | 
| nma_summary-class | The 'nma_summary' class | 
| nodesplit_summary | The 'nodesplit_summary' class | 
| nodesplit_summary-class | The 'nodesplit_summary' class | 
| normal | Prior distributions | 
| pairs.stan_nma | Matrix of plots for a 'stan_nma' object | 
| parkinsons | Mean off-time reduction in Parkison's disease | 
| pbern | The Bernoulli Distribution | 
| pgamma | The Gamma distribution | 
| pgent | Generalised Student's t distribution (with location and scale) | 
| plaque_psoriasis | Plaque psoriasis data | 
| plaque_psoriasis_agd | Plaque psoriasis data | 
| plaque_psoriasis_ipd | Plaque psoriasis data | 
| plogitnorm | The logit Normal distribution | 
| plogt | Log Student's t distribution | 
| plot.mcmc_array | Working with 3D MCMC arrays | 
| plot.nma_data | Network plots | 
| plot.nma_dic | Plots of model fit diagnostics | 
| plot.nma_nodesplit | Summarise the results of node-splitting models | 
| plot.nma_nodesplit_df | Summarise the results of node-splitting models | 
| plot.nma_parameter_summary | Plots of summary results | 
| plot.nma_rank_probs | Plots of summary results | 
| plot.nma_summary | Plots of summary results | 
| plot.nodesplit_summary | Plots of node-splitting models | 
| plot.stan_nma | Posterior summaries from 'stan_nma' objects | 
| plot.surv_nma_summary | Plots of summary results | 
| plot_integration_error | Plot numerical integration error | 
| plot_prior_posterior | Plot prior vs posterior distribution | 
| pmspline | Distribution functions for M-spline baseline hazards | 
| posterior_ranks | Treatment rankings and rank probabilities | 
| posterior_rank_probs | Treatment rankings and rank probabilities | 
| predict.stan_nma | Predictions of absolute effects from NMA models | 
| predict.stan_nma_surv | Predictions of absolute effects from NMA models | 
| print.mcmc_array | Working with 3D MCMC arrays | 
| print.mlnmr_data | Print 'nma_data' objects | 
| print.nma_data | Print 'nma_data' objects | 
| print.nma_dic | Methods for 'nma_dic' objects | 
| print.nma_nodesplit | Print 'nma_nodesplit_df' objects | 
| print.nma_nodesplit_df | Print 'nma_nodesplit_df' objects | 
| print.nma_summary | Methods for 'nma_summary' objects | 
| print.nodesplit_summary | Methods for 'nodesplit_summary' objects | 
| print.stan_nma | Print 'stan_nma' objects | 
| priors | Prior distributions | 
| qbern | The Bernoulli Distribution | 
| qgamma | The Gamma distribution | 
| qgent | Generalised Student's t distribution (with location and scale) | 
| qlogitnorm | The logit Normal distribution | 
| qlogt | Log Student's t distribution | 
| qmspline | Distribution functions for M-spline baseline hazards | 
| relative_effects | Relative treatment effects | 
| RE_cor | Random effects structure | 
| rmst_mspline | Distribution functions for M-spline baseline hazards | 
| set_agd_arm | Set up arm-based aggregate data | 
| set_agd_contrast | Set up contrast-based aggregate data | 
| set_agd_surv | Set up aggregate survival data | 
| set_ipd | Set up individual patient data | 
| smoking | Smoking cessation data | 
| social_anxiety | Social Anxiety | 
| softmax | Softmax transform | 
| stan_mlnmr | The stan_nma class | 
| stan_nma | The stan_nma class | 
| stan_nma-class | The stan_nma class | 
| statins | Statins for cholesterol lowering | 
| student_t | Prior distributions | 
| summary.mcmc_array | Working with 3D MCMC arrays | 
| summary.nma_nodesplit | Summarise the results of node-splitting models | 
| summary.nma_nodesplit_df | Summarise the results of node-splitting models | 
| summary.nma_prior | Summary of prior distributions | 
| summary.stan_nma | Posterior summaries from 'stan_nma' objects | 
| theme_multinma | Plot theme for multinma plots | 
| thrombolytics | Thrombolytic treatments data | 
| transfusion | Granulocyte transfusion in patients with neutropenia or neutrophil dysfunction | 
| unnest_integration | Add numerical integration points to aggregate data | 
| waic | Model comparison using the 'loo' package | 
| waic.stan_nma | Model comparison using the 'loo' package | 
| which_RE | Random effects structure | 
| .default | Set default values | 
| .is_default | Set default values |