Package: WARDEN 2.0.5

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

Toolkit to support and perform discrete event simulations with and without resource constraints in the context of health technology assessments (HTA). The package focuses on cost-effectiveness modelling and aims to be submission-ready to relevant HTA bodies in alignment with 'NICE TSD 15' <https://sheffield.ac.uk/nice-dsu/tsds/patient-level-simulation>. More details an examples can be found in the package website <https://jsanchezalv.github.io/WARDEN/>.

Authors:Javier Sanchez Alvarez [aut, cre], Gabriel Lemyre [ctb], Valerie Aponte Ribero [ctb]

WARDEN_2.0.5.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
WARDEN/json (API)

# Install 'WARDEN' in R:

install.packages('WARDEN', repos = c('https://jsanchezalv.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jsanchezalv/warden/issues

Pkgdown/docs site:https://jsanchezalv.github.io

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

tte.df - Example TTE IPD data

On CRAN:

cpp

6.66 score 12 stars 17 scripts 520 downloads 76 exports 64 dependencies

Last updated from:990feb44bf. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	265
linux-devel-x86_64	OK	234
source / vignettes	OK	275
linux-release-arm64	OK	263
linux-release-x86_64	OK	247
macos-release-arm64	OK	185
macos-release-x86_64	OK	403
macos-oldrel-arm64	OK	227
macos-oldrel-x86_64	OK	492
windows-devel	OK	205
windows-release	OK	208
windows-oldrel	OK	223
wasm-release	OK	198

Exports:add_item add_item2 add_reactevt add_tte adj_val ast_as_list ceac_des cond_dirichlet cond_mvn create_indicators disc_cycle disc_cycle_v disc_instant disc_instant_v disc_ongoing disc_ongoing_v discrete_resource_clone draw_tte evpi_des extract_elements_from_list extract_from_reactions extract_psa_result get_event has_event input_block luck_adj modify_event modify_item modify_item_seq new_event next_event next_event_pt pcond_gompertz pick_psa pick_val_v qbeta_mse qcond_exp qcond_gamma qcond_gompertz qcond_llogis qcond_lnorm qcond_norm qcond_weibull qcond_weibullPH qgamma_mse qtimecov queue_create queue_empty queue_size random_stream rbeta_mse rcond_gompertz rcond_gompertz_lu rdirichlet rdirichlet_prob release release_all release_all_if_using release_if_using remove_event replicate_profiles resource_discrete rgamma_mse rpoisgamma rpoisgamma_rcpp run_sim run_sim_parallel seize seize_all sens_iterator shared_decr shared_incr shared_input summary_results_det summary_results_sens summary_results_sim

Dependencies:assertthat bbmle bdsmatrix cli codetools cpp11 data.table deSolve digest doFuture dplyr farver fastGHQuad flexsurv foreach future future.apply generics ggplot2 globals glue gtable isoband iterators labeling lattice lifecycle listenv lsoda magrittr MASS Matrix mgcv mstate muhaz mvtnorm nlme numDeriv parallelly pillar pkgconfig progressr purrr quadprog R6 RColorBrewer Rcpp RcppArmadillo rlang rstpm2 S7 scales statmod stringi stringr survival tibble tidyr tidyselect utf8 vctrs viridisLite withr zoo

Example for a Sick-Sicker-Dead model

Rendered fromexample_ssd.Rmdusingknitr::rmarkdown

Last update: 2026-05-27
Started: 2021-10-22

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Define or append model inputs	add_item
Define parameters that may be used in model calculations (uses expressions)	add_item2
Define the modifications to other events, costs, utilities, or other items affected by the occurrence of the event	add_reactevt
Define events and the initial event time	add_tte
Adjusted Value Calculation	adj_val
Transform a substituted expression to its Abstract Syntax Tree (AST) as a list	ast_as_list
Calculate the cost-effectiveness acceptability curve (CEAC) for a DES model with a PSA result	ceac_des
Calculate conditional dirichlet values	cond_dirichlet
Calculate conditional multivariate normal values	cond_mvn
Creates a vector of indicators (0 and 1) for sensitivity/DSA analysis	create_indicators
Cycle discounting	disc_cycle
Cycle discounting for vectors	disc_cycle_v
Calculate instantaneous discounted costs or qalys	disc_instant
Calculate instantaneous discounted costs or qalys for vectors	disc_instant_v
Calculate discounted costs and qalys between events	disc_ongoing
Calculate discounted costs and qalys between events for vectors	disc_ongoing_v
Clone independent discrete resources	discrete_resource_clone
Draw a time to event from a list of parametric survival functions	draw_tte
Calculate the Expected Value of Perfect Information (EVPI) for a DES model with a PSA result	evpi_des
Extracts items and events by looking into assignments, modify_event and new_event	extract_elements_from_list
Extract all items and events and their interactions from the event reactions list	extract_from_reactions
Extract PSA results from a treatment	extract_psa_result
Get a specific event time	get_event
Check if a patient has a specific event in the queue	has_event
Build an input block for automatic parameter selection	input_block
Perform luck adjustment	luck_adj
Modify or add events for a patient	modify_event
Modify the value of existing items	modify_item
Modify the value of existing items	modify_item_seq
Add events to the queue for a patient	new_event
Get the next events in the queue	next_event
Get the next events in the queue for a specific patient	next_event_pt
Survival Probaility function for conditional Gompertz distribution (lower bound only)	pcond_gompertz
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'.	pick_psa
Select which values should be applied in the corresponding loop for several values (vector or list).	pick_val_v
Pop and return the next event	pop_and_return_event
Remove the next event from the queue	pop_event
Draw from a beta distribution based on mean and se (quantile)	qbeta_mse
Conditional quantile function for exponential distribution	qcond_exp
Conditional quantile function for gamma distribution	qcond_gamma
Quantile function for conditional Gompertz distribution (lower bound only)	qcond_gompertz
Conditional quantile function for loglogistic distribution	qcond_llogis
Conditional quantile function for lognormal distribution	qcond_lnorm
Conditional quantile function for normal distribution	qcond_norm
Conditional quantile function for weibull distribution	qcond_weibull
Conditional quantile function for WeibullPH (flexsurv)	qcond_weibullPH
Use quantiles from a gamma distribution based on mean and se	qgamma_mse
Draw time-to-event with time-dependent covariates and luck adjustment	qtimecov
Create a New Event Queue	queue_create
Check if the event queue is empty	queue_empty
Get the Size of the Event Queue	queue_size
Creates an environment (similar to R6 class) of random uniform numbers to be drawn from	random_stream
Draw from a beta distribution based on mean and se	rbeta_mse
Draw from a conditional Gompertz distribution (lower bound only)	rcond_gompertz
Draw from a conditional Gompertz distribution (lower and upper bound)	rcond_gompertz_lu
Draw from a dirichlet distribution based on number of counts in transition. Adapted from brms::rdirichlet	rdirichlet
Draw from a dirichlet distribution based on mean transition probabilities and standard errors	rdirichlet_prob
Release a discrete resource	release
Release multiple discrete resources	release_all
Release multiple discrete resources (using only)	release_all_if_using
Release a discrete resource only if using	release_if_using
Remove events for a patient	remove_event
Replicate profiles data.frame	replicate_profiles
Create a discrete resource	resource_discrete
Draw from a gamma distribution based on mean and se	rgamma_mse
Draw time to event (tte) from a Poisson or Poisson-Gamma (PG) Mixture/Negative Binomial (NB) Process	rpoisgamma
Draw time to event (tte) from a Poisson or Poisson-Gamma (PG) Mixture/Negative Binomial (NB) Process using C++	rpoisgamma_rcpp
Run the simulation	run_sim
Run simulations in parallel mode (at the simulation level)	run_sim_parallel
Seize a discrete resource	seize
Seize multiple discrete resources atomically	seize_all
Create an iterator based on sens of the current iteration within a scenario (DSA)	sens_iterator
Decrement a shared counter	shared_decr
Increment a shared counter	shared_incr
Shared input object	shared_input
Deterministic results for a specific treatment	summary_results_det
Summary of sensitivity outputs for a treatment	summary_results_sens
Summary of PSA outputs for a treatment	summary_results_sim
Example TTE IPD data	tte.df