README.md

In WARDEN: Workflows for Health Technology Assessments in R using Discrete EveNts

WARDEN: Workflows for health technology Assessments in R using Discrete EveNts

Introduction

WARDEN is a user-friendly package that facilitates the use of discrete event simulations without resource constraints for cost-effectiveness analysis. The package supports a flexible, practical approach to discrete event simulation while keeping an acceptable performance.

The current version supports:

• Discrete event simulation models, Markov/semi-Markov models and hybrid models using parallel and non-parallel engines
• Seamlessly integrating data.frames and other objects into the model
• Delayed execution of the main inputs to facilitate readability of the model
• Implementation of structural and parameter uncertainty
• Helper functions to facilitate drawing of time to events and the use of hazard ratios, as well as other functions to facilitate transparency
• Performing cost-effectiveness and uncertainty analysis

It is recommended that the user checks the vignettes, first the simple Sick-Sicker-Dead model and then the more complex model for early breast cancer. The markov example shows how to run a cohort Markov model while using the same modeling framework. Similarly, a simulation based Markov model could be run. Structural and parametric uncertainty are explored in the corresponding vignette. The IPD vignette shows how WARDEN can be used when individual patient data is available.

Documentation

Have a look at the package home site for more details on documentation and specific tutorials.

For more details on the code, check our Github repository or our CRAN site.

Installation

WARDEN can now be installed directly from CRAN or this repo via

install.packages("WARDEN") #CRAN version 

# install.packages("devtools")
devtools::install_github("jsanchezalv/WARDEN", ref="main") #github version

Citation

If you use WARDEN, please contact the authors for the most up to date appropriate citation.

WARDEN

WARDEN documentation built on April 11, 2025, 5:41 p.m.