aa_example_ndmm | Example newly-diagnosed multiple myeloma |
aa_example_pso_mlnmr | Example plaque psoriasis ML-NMR |
aa_example_smk_fe | Example smoking FE NMA |
aa_example_smk_nodesplit | Example smoking node-splitting |
aa_example_smk_re | Example smoking RE NMA |
aa_example_smk_ume | Example smoking UME NMA |
adapt_delta | Target average acceptance probability |
add_integration | Add numerical integration points to aggregate data |
as.array.stan_nma | Convert samples into arrays, matrices, or data frames |
as.stanfit | as.stanfit |
atrial_fibrillation | Stroke prevention in atrial fibrillation patients |
bcg_vaccine | BCG vaccination |
Bernoulli | The Bernoulli Distribution |
blocker | Beta blockers to prevent mortality after MI |
combine_network | Combine multiple data sources into one network |
default_values | Set default values |
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 |
GammaDist | The Gamma distribution |
generalised_t | Generalised Student's t distribution (with location and... |
geom_km | Kaplan-Meier curves of survival data |
get_nodesplits | Direct and indirect evidence |
graph_conversion | Convert networks to graph objects |
hta_psoriasis | HTA Plaque Psoriasis |
is_network_connected | Check network connectedness |
logitNormal | The logit Normal distribution |
log_t | Log Student's t distribution |
loo | Model comparison using the 'loo' package |
make_knots | Knot locations for M-spline baseline hazard models |
marginal_effects | Marginal treatment effects |
mcmc_array-class | Working with 3D MCMC arrays |
mspline | Distribution functions for M-spline baseline hazards |
multi | Multinomial outcome data |
multinma-package | multinma: A Package for Network Meta-Analysis of Individual... |
ndmm | Newly diagnosed multiple myeloma |
nma | Network meta-analysis models |
nma_data-class | The nma_data class |
nma_dic-class | The nma_dic class |
nma_dic-methods | Methods for 'nma_dic' objects |
nma_nodesplit-class | The nma_nodesplit class |
nma_prior-class | The nma_prior class |
nma_summary-class | The 'nma_summary' class |
nma_summary-methods | Methods for 'nma_summary' objects |
nodesplit_summary-class | The 'nodesplit_summary' class |
nodesplit_summary-methods | Methods for 'nodesplit_summary' objects |
pairs.stan_nma | Matrix of plots for a 'stan_nma' object |
parkinsons | Mean off-time reduction in Parkison's disease |
plaque_psoriasis | Plaque psoriasis data |
plot_integration_error | Plot numerical integration error |
plot.nma_data | Network plots |
plot.nma_dic | Plots of model fit diagnostics |
plot.nma_summary | Plots of summary results |
plot.nodesplit_summary | Plots of node-splitting models |
plot_prior_posterior | Plot prior vs posterior distribution |
posterior_ranks | Treatment rankings and rank probabilities |
predict.stan_nma | Predictions of absolute effects from NMA models |
print.nma_data | Print 'nma_data' objects |
print.nma_nodesplit_df | Print 'nma_nodesplit_df' objects |
print.stan_nma | Print 'stan_nma' objects |
priors | Prior distributions |
random_effects | Random effects structure |
reexports | Objects exported from other packages |
relative_effects | Relative treatment effects |
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_nma-class | The stan_nma class |
statins | Statins for cholesterol lowering |
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... |
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