Bayesian Network Meta-Analysis of Individual and Aggregate Data

Documentation for package ‘multinma’ version 0.7.1

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A B C D E F G H I L M N P Q R S T U W misc

multinma: A Package for Network Meta-Analysis of Individual and Aggregate Data in Stan

-- A --

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_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_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_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_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_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

-- B --

bcg_vaccine	BCG vaccination
blocker	Beta blockers to prevent mortality after MI

-- C --

cauchy	Prior distributions
combine_network	Combine multiple data sources into one network

-- D --

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

-- E --

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

-- F --

flat	Prior distributions

-- G --

geom_km	Kaplan-Meier curves of survival data
get_nodesplits	Direct and indirect evidence

-- H --

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

-- I --

is_network_connected

Check network connectedness

-- L --

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

-- M --

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

-- N --

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

-- P --

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	Print DIC details
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

-- Q --

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

-- R --

relative_effects	Relative treatment effects
RE_cor	Random effects structure
rmst_mspline	Distribution functions for M-spline baseline hazards

-- S --

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
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

-- T --

theme_multinma	Plot theme for multinma plots
thrombolytics	Thrombolytic treatments data
transfusion	Granulocyte transfusion in patients with neutropenia or neutrophil dysfunction

-- U --

unnest_integration

Add numerical integration points to aggregate data

-- W --

waic	Model comparison using the 'loo' package
waic.stan_nma	Model comparison using the 'loo' package
which_RE	Random effects structure

-- misc --

.default	Set default values
.is_default	Set default values