Health economic simulation modeling and decision analysis
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Updated
Sep 18, 2024 - R
Health economic simulation modeling and decision analysis
Bayesian Cost Effectiveness Analysis. 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 othe…
Survival analysis in health economic evaluation Contains a suite of functions to systematise the workflow involving survival analysis in health economic evaluation. survHE can fit a large range of survival models using both a frequentist approach (by calling the R package flexsurv) and a Bayesian perspective.
📈Markov Models for Health Economic Evaluations
Epidemiology modelling framework for the Thanzi la Onse project
Tools for building decision models for health technology assessment.
Collection of R Packages that support analysis for the purposes of Health Technology Assessment (HTA)
Speed up Discrete Markov Model Simulations.
Slides and Practicals for the BIDD modelling short course
Cost-Effectiveness Analysis for Clinical Trials
Health Economics simulation
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
PSA-ReD is a novel approach to the traditional scatterplot for displaying the results of Probabilistic Sensitivity Analysis. Here, we provide the script and an example dataset so that everyone can use this new and improved approach. This new approach is described in detail in the paper titled "Increasing the information provided by probabilistic…
R package that provides models and functions to fit non-standard NMAs: piecewise exponential models and fractional polynomial models for grouped survival data (derived from digitized Kaplan-Meier curves).
Short course on Bayesian methods for addressing missing data in health economic evaluations
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 matching-adjusted indirect comparison (MAIC) anaylsis for a disconnected treatment network where the endpoint of interest is either time-to-event (e.g. overall survival) or binary (e.g. objective tumor response).
R package that facilitates the use of discrete event simulations without resource constraints for cost-effectiveness analysis.
R package that extends the rpsftm package with some useful default reports and functions to facilitate sensitivity analysis. Covering descriptive, diagnostic and reporting aspects.
A suite of functions for the calculation and presentation of the Expected Value of Sample Information.
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