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

# Workflows for Health Technology Assessments in R using Discrete EveNts

## Documentation for package ‘WARDEN’ version 2.0.3

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

add_item | Define or append model inputs
add_item2 | Define parameters that may be used in model calculations (uses expressions)
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
adj_val | Adjusted Value Calculation
ast_as_list | Transform a substituted expression to its Abstract Syntax Tree (AST) as a list
ceac_des | Calculate the cost-effectiveness acceptability curve (CEAC) for a DES model with a PSA result
cond_dirichlet | Calculate conditional dirichlet values
cond_mvn | Calculate conditional multivariate normal values
create_indicators | Creates a vector of indicators (0 and 1) for sensitivity/DSA analysis
discrete_resource_clone | Clone independent discrete resources
disc_cycle | Cycle discounting
disc_cycle_v | Cycle discounting for vectors
disc_instant | Calculate instantaneous discounted costs or qalys
disc_instant_v | Calculate instantaneous discounted costs or qalys for vectors
disc_ongoing | Calculate discounted costs and qalys between events
disc_ongoing_v | Calculate discounted costs and qalys between events for vectors
draw_tte | Draw a time to event from a list of parametric survival functions
evpi_des | Calculate the Expected Value of Perfect Information (EVPI) for a DES model with a PSA result
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
get_event | Get a specific event time
has_event | Check if a patient has a specific event in the queue
input_block | Build an input block for automatic parameter selection
luck_adj | Perform luck adjustment
modify_event | Modify or add events for a patient
modify_item | Modify the value of existing items
modify_item_seq | Modify the value of existing items
new_event | Add events to the queue for a patient
next_event | Get the next events in the queue
next_event_pt | Get the next events in the queue for a specific patient
pcond_gompertz | Survival Probaility function for conditional Gompertz distribution (lower bound only)
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).
pop_and_return_event | Pop and return the next event
pop_event | Remove the next event from the queue
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)
qgamma_mse | Use quantiles from a gamma distribution based on mean and se
qtimecov | Draw time-to-event with time-dependent covariates and luck adjustment
queue_create | Create a New Event Queue
queue_empty | Check if the event queue is empty
queue_size | Get the Size of the Event Queue
random_stream | Creates an environment (similar to R6 class) of random uniform numbers to be drawn from
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
remove_event | Remove events for a patient
replicate_profiles | Replicate profiles data.frame
resource_discrete | Create a discrete resource
rgamma_mse | Draw 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++
run_sim | Run the simulation
run_sim_parallel | Run simulations in parallel mode (at the simulation level)
sens_iterator | Create an iterator based on sens of the current iteration within a scenario (DSA)
shared_input | Shared input object
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
tte.df | Example TTE IPD data