Decision tree to Markov models using S3 tutorial code

A R package with utility functions to be used mainly for post-processing (of Bayesian models)

A Python-based tool for building and analyzing decision trees in pharmacoeconomics.

R and Julia codes for case study 2 (Breast Cancer toxicity model) in the manuscript titled "Adding noise to Markov cohort state-transition models."

CEA tool and analysis of costs and health outcomes for interventions that increase contraceptive access in Nigeria

Cost-effectiveness analysis comparing two interventions with probabilistic sensitivity analysis.

Model agnostic cost effectiveness plotting

Reproducible cost-effectiveness modeling

Code for the cost-effectiveness analysis of a salt substitute intervention in Northern Peru. Includes R code but no datasets.

Survival analysis in health economic evaluation using Bayesian modelling though Integrated Nested Laplace Approximation. Contains a suite of functions to systematise the workflow involving survival analysis in health economic evaluation.

R codes for the example in the paper titled "A theoretical framework for state-transition cohort model in health decision analysis," https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0205543

A math language for dimensional analysis

R code for the case study in the manuscript titled "Probability bound analysis: A novel approach for quantifying parameter uncertainty in decision-analytic modeling and cost-effectiveness analysis."

Cost effectiveness analysis of maternal vaccines and monoclonal antibodies against RSV in Kenya and South Africa

Short course on Bayesian methods for addressing missing data in health economic evaluations

Code repository for "A Sensitivity Analysis Framework for Health Economic Evaluation in Middle Income Countries: Appropriately Incorporating a Comprehensive Approach"

A R/Shiny frontend to use BCEA

Tools for building decision models for health technology assessment.

R for trial and model-based cost-effectiveness analysis: One-day workshop

Health economic evaluations from individual level data with missing values using a set of pre-defined Bayesian models written in BUGS. A series of parametric models are available to jointly model partially-observed effectiveness and cost outcomes under both ignorable and nonignroable missing data mechanism assumptions