Package index • WARDEN

Main Modelling Functions

Core Functions

run_sim(): Run the simulation

run_sim_parallel(): Run simulations in parallel mode (at the simulation level)

add_item(): Define or append model inputs

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

add_tte(): Define events and the initial event time

new_event(): Add Events to the Queue for a Patient

modify_event(): Modify or Add Events for a Patient

remove_event(): Remove Events for a Patient

get_event(): Get a specific event time

has_event(): Check if a Patient Has a Specific Event

next_event(): Get the Next Event(s) in the Queue

next_event_pt(): Get the Next Event(s) in the Queue for a specific patient

queue_empty(): Check if the Event Queue is Empty

queue_size(): Get the Size of the Event Queue

queue_create(): Create a New Event Queue

pop_event(): Remove the Next Event from the Queue

pop_and_return_event(): Pop and Return the Next Event

Resource Constrained Specific Functions

resource_discrete(): Create a Discrete Resource

shared_input(): Shared input object

discrete_resource_clone(): Clone independent discrete resources

Auxiliary Functions

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

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

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

replicate_profiles(): Replicate profiles data.frame

Summary Functions

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

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

summary_results_det(): Deterministic results for a specific treatment

summary_results_sens(): Summary of sensitivity outputs for a treatment

summary_results_sim(): Summary of PSA outputs for a treatment

Statistics Functions

Auxiliary Functions

draw_tte(): Draw a time to event from a list of parametric survival functions

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

luck_adj(): Perform luck adjustment

qtimecov(): Draw Time-to-Event with Time-Dependent Covariates and Luck Adjustment

adj_val(): Adjusted Value Calculation

Distributions Functions

cond_dirichlet(): Calculate conditional dirichlet values

cond_mvn(): Calculate conditional multivariate normal values

rgamma_mse(): Draw from a gamma distribution based on mean and se

qgamma_mse(): Use quantiles from a gamma distribution based on mean and se

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

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

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

qcond_exp(): Conditional quantile function for exponential distribution

qcond_gamma(): Conditional quantile function for gamma distribution

qcond_gompertz(): Quantile function for conditional Gompertz distribution (lower bound only)

qcond_llogis(): Conditional quantile function for loglogistic distribution

qcond_lnorm(): Conditional quantile function for lognormal distribution

qcond_norm(): Conditional quantile function for normal distribution

qcond_weibull(): Conditional quantile function for weibull distribution

qcond_weibullPH(): Conditional quantile function for WeibullPH (flexsurv)

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

rcond_gompertz(): Draw from a conditional Gompertz distribution (lower bound only)

rcond_gompertz_lu(): Draw from a Conditional Gompertz distribution (lower and upper bound)

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

rdirichlet_prob(): Draw from a dirichlet distribution based on mean transition probabilities and standard errors

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

Other Functions and Utilities

disc_cycle_v(): Cycle discounting for vectors

disc_instant_v(): Calculate instantaneous discounted costs or qalys for vectors

disc_ongoing_v(): Calculate discounted costs and qalys between events for vectors

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

extract_elements_from_list(): Extracts items and events by looking into assignments, modify_event and new_event

extract_from_reactions(): Extract all items and events and their interactions from the event reactions list

extract_psa_result(): Extract PSA results from a treatment

tte.df: Example TTE IPD data

Deprecated Functions

add_item2(): Define parameters that may be used in model calculations (uses expressions)

modify_item(): Modify the value of existing items

modify_item_seq(): Modify the value of existing items

disc_cycle(): Cycle discounting

disc_instant(): Calculate instantaneous discounted costs or qalys

disc_ongoing(): Calculate discounted costs and qalys between events