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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 with or without resource constraints for cost-effectiveness analysis. The package supports a flexible, transparent, 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
Constrained and unconstrained models (with or without interactivity between patients)
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. It is also suggested to check the constrained resources DES example on the website.

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

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Version

Install

install.packages('WARDEN')

Monthly Downloads

349

Version

2.0.6

License

GPL (>= 3)

Maintainer

Javier Sanchez Alvarez

Last Published

July 23rd, 2026

Functions in WARDEN (2.0.6)

Define parameters that may be used in model calculations (uses expressions)

Calculate discounted costs and qalys between events

discrete_resource_clone

Clone independent discrete resources

.resource_discrete_from_xptr

Creates a discrete resource from an external pointer

pop_and_return_event

Pop and return the next event

extract_psa_result

Extract PSA results from a treatment

extract_from_reactions

Extract all items and events and their interactions from the event reactions list

Select which values should be applied in the corresponding loop for several values (vector or list).

Draw a time to event from a list of parametric survival functions

Add events to the queue for a patient

Get a specific event time

modify_item_seq

Modify the value of existing items

Calculate instantaneous discounted costs or qalys for vectors

Check if a patient has a specific event in the queue

Cycle discounting

Conditional quantile function for loglogistic distribution

Conditional quantile function for lognormal distribution

Calculate instantaneous discounted costs or qalys

Calculate discounted costs and qalys between events for vectors

Cycle discounting for vectors

Conditional quantile function for normal distribution

Conditional quantile function for weibull distribution

rcond_gompertz_lu

Draw from a conditional Gompertz distribution (lower and upper bound)

Perform luck adjustment

Survival Probaility function for conditional Gompertz distribution (lower bound only)

Helper function to create a list with random draws or whenever a series of functions needs to be called. Can be implemented within pick_val_v.

release_all_if_using

Release multiple discrete resources (using only)

draw_categorical

Draw a categorical index from probabilities

Build an input block for automatic parameter selection

Check if the event queue is empty

print.resource_discrete

Print method for resource_discrete

Quantile function for conditional Gompertz distribution (lower bound only)

Draw from a conditional Gompertz distribution (lower bound only)

qcond_weibullPH

Conditional quantile function for WeibullPH (flexsurv)

Use quantiles from a gamma distribution based on mean and se

Modify or add events for a patient

Modify the value of existing items

print.warden_results

Print method for warden_results

Remove the next event from the queue

Draw from a beta distribution based on mean and se (quantile)

release_if_using

Release a discrete resource only if using

Draw time to event (tte) from a Poisson or Poisson-Gamma (PG) Mixture/Negative Binomial (NB) Process

Decrement a shared counter

Compute effective hazard ratio with treatment waning

rpoisgamma_rcpp

Draw time to event (tte) from a Poisson or Poisson-Gamma (PG) Mixture/Negative Binomial (NB) Process using C++

with_write_flags_lang

Evaluate a language object with write-tracking via active bindings

Release a discrete resource

Creates an environment (similar to R6 class) of random uniform numbers to be drawn from

Increment a shared counter

Draw from a gamma distribution based on mean and se

Draw from a beta distribution based on mean and se

Conditional quantile function for exponential distribution

rdirichlet_prob

Draw from a dirichlet distribution based on mean transition probabilities and standard errors

Quantile function for categorical distribution

resource_discrete

Create a discrete resource

Release multiple discrete resources

Get the Size of the Event Queue

Draw from a dirichlet distribution based on number of counts in transition. Adapted from brms::rdirichlet

scale_remaining_time

Scale remaining time to an event by a hazard ratio

replicate_profiles

Replicate profiles data.frame

summary_results_sim

Summary of PSA outputs for a treatment

extract_elements_from_list

Extracts items and events by looking into assignments, modify_event and new_event

Create a New Event Queue

Remove events for a patient

summary_results_sens

Summary of sensitivity outputs for a treatment

Create an iterator based on sens of the current iteration within a scenario (DSA)

Seize multiple discrete resources atomically

Seize a discrete resource

summary_results_det

Deterministic results for a specific treatment

Shared input object

Calculate the Expected Value of Perfect Information (EVPI) for a DES model with a PSA result

Get the next events in the queue for a specific patient

run_sim_parallel

Run simulations in parallel mode (at the simulation level)

Run the simulation

Get the next events in the queue

Validate model inputs before running

Conditional quantile function for gamma distribution

Draw time-to-event with time-dependent covariates and luck adjustment

Example TTE IPD data

Calculate conditional dirichlet values

Define events and the initial event time

Define the modifications to other events, costs, utilities, or other items affected by the occurrence of the event

Transform a substituted expression to its Abstract Syntax Tree (AST) as a list

create_indicators

Creates a vector of indicators (0 and 1) for sensitivity/DSA analysis

Adjusted Value Calculation

Define or append model inputs

Calculate the cost-effectiveness acceptability curve (CEAC) for a DES model with a PSA result

Calculate conditional multivariate normal values