Tools for building decision models for health technology assessment.
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Updated
Jun 3, 2024 - R
Tools for building decision models for health technology assessment.
Collection of R Packages that support analysis for the purposes of Health Technology Assessment (HTA)
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
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
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."
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 package that facilitates performing survival analysis to support the creation of Excel based economic models by providing helper functions to use alongside the flexsurv package.
Code repository for "A Sensitivity Analysis Framework for Health Economic Evaluation in Middle Income Countries: Appropriately Incorporating a Comprehensive Approach"
Model agnostic cost effectiveness plotting
Cost effectiveness analysis of maternal vaccines and monoclonal antibodies against RSV in Kenya and South Africa
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