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BCEA: Bayesian cost-effectiveness analysis

Perform Bayesian Cost-Effectiveness Analysis in R.

:rocket: Version 2.4.3 out now! Check out the release notes here.

Contents

Overview

Given the results of a Bayesian model (possibly based on MCMC) in the form of simulations from the posterior distributions of suitable variables of costs and clinical benefits for two or more interventions, produces a health economic evaluation. Compares one of the interventions (the "reference") to the others ("comparators").

Features

Main features of BCEA include:

  • Cost-effectiveness analysis plots, such as CE planes and CEAC
  • Summary statistics and tables
  • EVPPI calculations and plots

Installation

Install the released version from CRAN with

install.packages("BCEA")

The stable version (which can be updated more quickly) can be installed using this GitHub repository. On Windows machines, you need to install a few dependencies, including Rtools first, e.g. by running

pkgs <- c("MASS", "Rtools", "remotes")
repos <- c("https://cran.rstudio.com", "https://inla.r-inla-download.org/R/stable/") 
install.packages(pkgs, repos=repos, dependencies = "Depends")

before installing the package using remotes:

remotes::install_github("giabaio/BCEA")

Under Linux or MacOS, it is sufficient to install the package via remotes:

install.packages("remotes")
remotes::install_github("giabaio/BCEA")

Articles

Examples of using specific functions and their different arguments are given in these articles:

Further details

The pkgdown site is here. More details on BCEA are available in our book Bayesian Cost-Effectiveness Analysis with the R Package BCEA (published in the UseR! Springer series). Also, details about the package, including some references and links to a pdf presentation and some posts on my own blog) are given here.

License

Contributing

Please submit contributions through Pull Requests, following the contributing guidelines. To report issues and/or seek support, please file a new ticket in the issue tracker.

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

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Version

Install

install.packages('BCEA')

Monthly Downloads

3,822

Version

2.4.4

License

GPL-3

Issues

Pull Requests

Stars

Forks

Maintainer

Gianluca Baio

Last Published

June 5th, 2023

Functions in BCEA (2.4.4)

bcea

Create Bayesian Cost-Effectiveness Analysis Object
CEriskav_assign

Cost-effectiveness Analysis Including a Parameter of Risk Aversion
CEriskav_plot_graph

Cost-effectiveness Plot Including a Parameter of Risk Aversion
BCEA-package

BCEA: Bayesian Cost Effectiveness Analysis
BCEA-deprecated

Deprecated functions in package BCEA.
add_contours

Add Contours to Base R Plot
best_interv_given_k

Optimal intervention
ceef_plot_graph

Cost-effectiveness Efficiency Frontier Plot By Graph Device
GrassmannOptim

GrassmannOptim
ceac.plot.bcea

Cost-Effectiveness Acceptability Curve (CEAC) Plot
ceaf.plot.pairwise

Cost-Effectiveness Acceptability Frontier (CEAF) plot
ceac_matplot

CEAC Matrix Plot
ceef.plot.bcea

Cost-Effectiveness Efficiency Frontier (CEEF) Plot
ceac_plot_graph

Cost-Effectiveness Acceptability Curve (CEAC) Plot By Graph Device
add_contour_quadrants

Add Contour Quadrants
ceplane.plot.bcea

Cost-effectiveness Plane Plot
ce_table

Cost-effectiveness summary statistics table
ceef.summary

Summary table for CEEF
compute_EVI

Compute Expected Value of Information
ceplane_geom_params

Extract Separate Parameter Sets
ceplane_ggplot_params

CE-plane ggplot Parameters
compute_IB

Compute Incremental Benefit
compute_U

Compute U Statistic
compute_ICER

Compute Incremental Cost-Effectiveness Ratio
compute_CEAC

Compute Cost-Effectiveness Acceptability Curve
compute_p_best_interv

Compute Probability Best Intervention
compute_EIB

Compute Expected Incremental Benefit
compute_ol

Compute Opportunity Loss
contour.bcea

Contour Plots for the Cost-Effectiveness Plane
compute_vi

Compute Value of Information
compute_eib_cri

Calculate Credible Intervals
compute_ceaf

Compute Cost-Effectiveness Acceptability Frontier
createInputs.default

Create Inputs for EVPI Calculation
compute_kstar

Compute k^*
diag.evppi

Diagnostic Plots For The Results Of The EVPPI
compute_evppi

Compute EVPPI
eib_plot_graph

Expected Incremental Benefit Plot By Graph Device
eib_params_cri

EIB Parameters CrI
evi.plot.mixedAn

EVI Plot of the Health Economic Analysis For Mixed Analysis
evi_plot_graph

Expected Value of Information Plot By Graph Device
contour_ggplot_params

Contour ggplot Parameters
contour2.bcea

Specialised CE-plane Contour Plot
fit.gam

Gaussian Additive Model Fitting
fit.gp

Fit Gaussian Process
is.bcea

Check bcea Class
contour_graph

Contour Cost-Effectiveness Plane
estimate.hyperparams

Estimate hyperparameters
convert_pts_to_mm

Use from Base R to ggplot
eib_params_base

EIB parameters specific to base R plot
evppi

Expected Value of Perfect Partial Information (EVPPI) for Selected Parameters
evppi_plot_graph

Plot Expected Value of Partial Information With Respect to a Set of Parameters
info_rank_graph

Info Rank Plot By Graph Device
kstar_vlines

Prepare K-star vertical lines
eib.plot.bcea

Expected Incremental Benefit (EIB) Plot
evi.plot.bcea

Expected Value of Information (EVI) Plot
new_bcea

Constructor for bcea
num_lines

Get number of lines
inforank_params

Prepare Info Rank plot parameters
ceplane_plot_graph

Cost-Effectiveness Plane Plot By Graph Device
ib_plot_base

IB plot base R version
comp_names_from_

Comparison Names From
loo_rank

Leave-one-out ranking
line_labels

Create Labels for Plot
multiplot

Plot Multiple bcea Graphs
multi.ce

Cost-effectiveness Analysis With Multiple Comparison
prep_frontier_data

Prepare frontier data
plot.bcea

Summary Plot of the Health Economic Analysis
prepare.output

Prepare output
info.rank.bcea

Information-Rank Plot for bcea Class
plot.evppi

Plot Expected Value of Partial Information With Respect to a Set of Parameters
make.report

Make Report
setKmax_assign

Set Maximum Willingness to Pay
mce.plot

Plots the probability that each intervention is the most cost-effective
setReferenceGroup_assign

Set Reference Group
compute_Ustar

Compute Ustar Statistic
make_legend_plotly

Legend Positioning
summary.pairwise

Summary Method for Objects of Class pairwise
validate_eib_params

Validate EIB parameters
plot_mesh

Mesh Plot
prep_ceplane_params

Prepare CE-plane Parameters
plot_eib_cri

Plot Credible Intervals
compute_Ubar

Compute NB for mixture of interventions
prep_eib_params

Prepare EIB plot parameters
print.bcea

bcea Print Method
theme_bcea

bcea theme ggplot2
geom_cri

Credible interval ggplot geom
mixedAn<-

Cost-Effectiveness Analysis When Multiple (Possibly Non-Cost-Effective) Interventions are Present on the Market
tabulate_means

Calculate Dataset For ICERs From bcea Object
ib.plot.bcea

Incremental Benefit (IB) Distribution Plot
make.mesh

Make Mesh
fit.inla

Fit using INLA
summary.mixedAn

Summary Methods For Objects in the Class mixedAn (Mixed Analysis)
make.proj

INLA Fitting
summary.bcea

Summary Method for Objects of Class bcea
quadrant_params

Quadrant Parameters requires just a single comparison group
geom_quad_txt

Geom Quadrant Text
validate_bcea

Validate bcea
quiet

Allow disabling of the cat messages
post.density

Gaussian Process Fitting
plot.CEriskav

Plots EIB and EVPI for the Risk Aversion Case
openPDF

Automatically open pdf output using default pdf viewer
setComparisons_assign

Set Comparison Group
setComparisons

Set Comparisons Group
struct.psa

Structural Probability Sensitivity Analysis
select_plot_type

Choose Graphical Engine
prep.x

Prepare Delta arrays
sim_table

Table of Simulation Statistics for the Health Economic Model
Vaccine

Data set for the Bayesian model for the cost-effectiveness of influenza vaccination
Smoking

Data set for the Bayesian model for the cost-effectiveness of smoking cessation interventions