Function reference • hesim

Fitted statistical models
`flexsurvreg_list()`	List of `flexsurvreg` objects
`multinom_list()`	List of `multinom` objects
`partsurvfit()`	Partitioned survival regression object
Probability distributions
`mom_beta()`	Method of moments for beta distribution
`mom_gamma()`	Method of moments for gamma distribution
`fast_rgengamma()`	Random generation for generalized gamma distribution
`rcat()`	Random generation for categorical distribution
`rpwexp()`	Random generation for piecewise exponential distribution
`rdirichlet_mat()`	Random generation for multiple Dirichlet distributions
Transition matrices
`tpmatrix()`	Transition probability matrix
`tpmatrix_id()`	Transition probability matrix IDs
`tpmatrix_names()`	Names for elements of a transition probability matrix
`summary(<tpmatrix>)`	Summarize transition probability matrix
`qmatrix(<matrix>)` `qmatrix(<data.table>)` `qmatrix(<data.frame>)`	Transition intensity matrix from tabular object
`qmatrix(<msm>)`	Transition intensity matrix from `msm` object
`expmat()`	Matrix exponential
`as_array3()` `as_tbl2()`	Convert between 2D tabular objects and 3D arrays
`apply_rr()`	Apply relative risks to transition probability matrices
Parameters
`params`	Parameter object
`create_params()`	Create a parameter object from a fitted model
`params_lm()`	Parameters of a linear model
`params_mlogit()`	Parameters of a multinomial logit model
`params_mlogit_list()`	Parameters of a list of multinomial logit models
`params_surv()`	Parameters of a survival model
`params_surv_list()`	Parameters of a list of survival models
`summary(<params_lm>)` `summary(<params_mlogit>)` `summary(<params_mlogit_list>)` `summary(<params_surv>)` `summary(<params_surv_list>)`	Summarize parameter objects
`tparams`	Transformed parameter object
`tparams_mean()`	Predicted means
`summary(<tparams_mean>)` `print(<tparams_mean>)`	Summarize `tparams_mean` object
`tparams_transprobs()`	Transition probabilities
`as.data.table(<tparams_transprobs>)`	Coerce to `data.table`
`summary(<tparams_transprobs>)`	Summarize `tparams_transprobs` object
Input data
`hesim_data()`	Data for health economic simulation modeling
`expand(<hesim_data>)`	Expand hesim_data
`create_trans_dt()`	Create a data table of health state transitions
`time_intervals()`	Time intervals
`input_mats()` `as.data.table(<input_mats>)` `print(<input_mats>)`	Input matrices for a statistical model
`get_labels()`	Get value labels
`set_labels()`	Set value labels
Model definition
`beta_rng()` `dirichlet_rng()` `fixed()` `custom()` `gamma_rng()` `lognormal_rng()` `multi_normal_rng()` `normal_rng()` `uniform_rng()`	Random number generation distributions
`define_rng()` `eval_rng()`	Define and evaluate random number generation expressions
`summary(<eval_rng>)` `print(<eval_rng>)`	Summarize `eval_rng` object
`define_tparams()` `eval_tparams()`	Define and evaluate transformed parameter expressions
`define_model()` `eval_model()`	Define and evaluate model expression
Health state values
`stateval_tbl()`	Table to store state value parameters
`StateVals`	Model for state values
`create_StateVals()`	Create a `StateVals` object
Discrete time state transition model
`CohortDtstmTrans`	Transitions for a cohort discrete time state transition model
`create_CohortDtstmTrans()`	Create `CohortDtstmTrans` object
`CohortDtstm`	Cohort discrete time state transition model
`create_CohortDtstm()`	Create `CohortDtstm` object
Partitioned survival model
`Psm`	N-state partitioned survival model
`PsmCurves`	Partitioned survival curves
`create_PsmCurves()`	Create `PsmCurves` object
Continuous time state transition model
`IndivCtstmTrans`	Transitions for an individual-level continuous time state transition model
`create_IndivCtstmTrans()`	Create `IndivCtstmTrans` object
`IndivCtstm`	Individual-level continuous time state transition model
General simulation functions and output
`disprog`	Disease progression object
`survival()`	Survival object
`sim_stateprobs(<survival>)`	Simulate state probabilities from survival curves
`stateprobs`	State probability object
`sim_ev(<stateprobs>)` `sim_qalys()` `sim_costs()`	Expected values from state probabilities
`costs`	Costs object
`qalys`	Quality-adjusted life-years object
`ce`	A cost-effectiveness object
Summarize outcomes
`incr_effect()`	Incremental treatment effect
`surv_quantile()`	Survival quantiles
`summary(<ce>)` `format(<summary.ce>)`	Summary method for cost-effectiveness object
Cost-effectiveness analysis
`cea()` `cea_pw()`	Cost-effectiveness analysis
`icer()` `format(<icer>)`	Incremental cost-effectiveness ratio
Plotting
`autoplot(<survival>)`	Plot survival curves
`autoplot(<stateprobs>)`	Plot state probabilities
`plot_ceplane()`	Plot cost-effectiveness plane
`plot_ceac()`	Plot cost-effectiveness acceptability curve
`plot_ceaf()`	Plot cost-effectiveness acceptability frontier
`plot_evpi()`	Plot expected value of perfect information
Datasets
`mstate3_exdata`	Example data for a reversible 3-state multi-state model
`multinom3_exdata`	Example data for a 3-state multinomial model
`psm4_exdata`	Example data for a 4-state partitioned survival model
`onc3`	Multi-state oncology data for 3-state model
`onc3p`	Multi-state panel oncology data for 3-state model
`as_pfs_os()`	Convert multi-state data to PFS and OS data

Reference

Fitted statistical models

Probability distributions

Transition matrices

Parameters

Input data

Model definition

Health state values

Discrete time state transition model

Partitioned survival model

Continuous time state transition model

General simulation functions and output

Summarize outcomes

Cost-effectiveness analysis

Plotting

Datasets