# Health Economic Simulation Modeling and Decision Analysis

## Documentation for package ‘hesim’ version 0.5.2

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

## Help Pages

A B C D E F G H I L M N O P Q R S T U W

## -- A --

apply_rr | Apply relative risks to transition probability matrices
as.data.table.input_mats | Input matrices for a statistical model
as.data.table.tparams_transprobs | Coerce to 'data.table'
as_array3 | Convert between 2D tabular objects and 3D arrays
as_pfs_os | Convert multi-state data to PFS and OS data
as_tbl2 | Convert between 2D tabular objects and 3D arrays
autoplot.stateprobs | Plot state probabilities
autoplot.survival | Plot survival curves

## -- B --

beta_rng | Random number generation distributions

## -- C --

ce | A cost-effectiveness object
cea | Cost-effectiveness analysis
cea.ce | Cost-effectiveness analysis
cea.default | Cost-effectiveness analysis
cea_pw | Cost-effectiveness analysis
cea_pw.ce | Cost-effectiveness analysis
cea_pw.default | Cost-effectiveness analysis
check_input_data | Check input data argument for 'create_input_mats'
CohortDtstm | Cohort discrete time state transition model
CohortDtstmTrans | Transitions for a cohort discrete time state transition model
costs | Costs object
create_CohortDtstm | Create 'CohortDtstm' object
create_CohortDtstm.model_def | Create 'CohortDtstm' object
create_CohortDtstmTrans | Create 'CohortDtstmTrans' object
create_CohortDtstmTrans.msm | Create 'CohortDtstmTrans' object
create_CohortDtstmTrans.multinom_list | Create 'CohortDtstmTrans' object
create_CohortDtstmTrans.params_mlogit_list | Create 'CohortDtstmTrans' object
create_IndivCtstmTrans | Create 'IndivCtstmTrans' object
create_IndivCtstmTrans.flexsurvreg | Create 'IndivCtstmTrans' object
create_IndivCtstmTrans.flexsurvreg_list | Create 'IndivCtstmTrans' object
create_IndivCtstmTrans.params_surv | Create 'IndivCtstmTrans' object
create_IndivCtstmTrans.params_surv_list | Create 'IndivCtstmTrans' object
create_input_mats | Create input matrices
create_input_mats.flexsurvreg | Create input matrices
create_input_mats.flexsurvreg_list | Create input matrices
create_input_mats.lm | Create input matrices
create_input_mats.multinom | Create input matrices
create_input_mats.multinom_list | Create input matrices
create_input_mats.params_lm | Create input matrices
create_input_mats.params_mlogit_list | Create input matrices
create_input_mats.params_surv | Create input matrices
create_input_mats.params_surv_list | Create input matrices
create_input_mats.partsurvfit | Create input matrices
create_lines_dt | Create a data table of treatment lines
create_params | Create a parameter object from a fitted model
create_params.flexsurvreg | Create a parameter object from a fitted model
create_params.flexsurvreg_list | Create a parameter object from a fitted model
create_params.lm | Create a parameter object from a fitted model
create_params.multinom | Create a parameter object from a fitted model
create_params.multinom_list | Create a parameter object from a fitted model
create_params.partsurvfit | Create a parameter object from a fitted model
create_PsmCurves | Create 'PsmCurves' object
create_PsmCurves.flexsurvreg_list | Create 'PsmCurves' object
create_PsmCurves.params_surv_list | Create 'PsmCurves' object
create_StateVals | Create a 'StateVals' object
create_StateVals.lm | Create a 'StateVals' object
create_StateVals.stateval_tbl | Create a 'StateVals' object
create_trans_dt | Create a data table of health state transitions
CtstmTrans | An 'R6' base class for continuous time state transition models
custom | Random number generation distributions

## -- D --

define_model | Define and evaluate model expression
define_rng | Define and evaluate random number generation expressions
define_tparams | Define and evaluate transformed parameter expressions
dirichlet_rng | Random number generation distributions
disprog | Disease progression object
dweibullNMA | Parameterization of the Weibull distribution for network meta-analysis

## -- E --

eval_model | Define and evaluate model expression
eval_rng | Define and evaluate random number generation expressions
eval_tparams | Define and evaluate transformed parameter expressions
expand.hesim_data | Expand hesim_data
expmat | Matrix exponential

## -- F --

fast_rgengamma | Random generation for generalized gamma distribution
fixed | Random number generation distributions
flexsurvreg_list | List of 'flexsurvreg' objects
format.icer | Incremental cost-effectiveness ratio
format.summary.ce | Summary method for cost-effectiveness object

## -- G --

gamma_rng | Random number generation distributions
get_labels | Get value labels

## -- H --

hesim | 'hesim': Health Economic Simulation Modeling and Decision Analysis
hesim_data | Data for health economic simulation modeling
hesim_survdists | List of survival distributions
HweibullNMA | Parameterization of the Weibull distribution for network meta-analysis
hweibullNMA | Parameterization of the Weibull distribution for network meta-analysis

## -- I --

icea | Individualized cost-effectiveness analysis
icea_pw | Individualized cost-effectiveness analysis
icer | Incremental cost-effectiveness ratio
icer_tbl | ICER table
id_attributes | Attributes for ID variables
incr_effect | Incremental treatment effect
IndivCtstm | Individual-level continuous time state transition model
IndivCtstmTrans | Transitions for an individual-level continuous time state transition model
input_mats | Input matrices for a statistical model

## -- L --

lognormal_rng | Random number generation distributions

## -- M --

mean_weibullNMA | Parameterization of the Weibull distribution for network meta-analysis
mom_beta | Method of moments for beta distribution
mom_gamma | Method of moments for gamma distribution
mstate3_exdata | Example data for a reversible 3-state multi-state model
multinom3_exdata | Example data for a 3-state multinomial model
multinom_list | List of 'multinom' objects
multi_normal_rng | Random number generation distributions

## -- N --

normal_rng | Random number generation distributions

## -- O --

onc3 | Multi-state oncology data for 3-state model
onc3p | Multi-state panel oncology data for 3-state model

## -- P --

params | Parameter object
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
plot_ceac | Plot cost-effectiveness acceptability curve
plot_ceac.cea | Plot cost-effectiveness acceptability curve
plot_ceac.cea_pw | Plot cost-effectiveness acceptability curve
plot_ceaf | Plot cost-effectiveness acceptability frontier
plot_ceplane | Plot cost-effectiveness plane
plot_evpi | Plot expected value of perfect information
print.eval_rng | Summarize 'eval_rng' object
print.input_mats | Input matrices for a statistical model
print.params_mlogit | Parameters of a multinomial logit model
print.params_surv | Parameters of a survival model
print.tparams_mean | Summarize 'tparams_mean' object
print.tparams_transprobs | Transition probabilities
Psm | N-state partitioned survival model
psm4_exdata | Example data for a 4-state partitioned survival model
PsmCurves | Partitioned survival curves
pweibullNMA | Parameterization of the Weibull distribution for network meta-analysis

## -- Q --

qalys | Quality-adjusted life-years object
qmatrix | Transition intensity matrix
qmatrix.data.frame | Transition intensity matrix from tabular object
qmatrix.data.table | Transition intensity matrix from tabular object
qmatrix.matrix | Transition intensity matrix from tabular object
qmatrix.msm | Transition intensity matrix from 'msm' object
qweibullNMA | Parameterization of the Weibull distribution for network meta-analysis

## -- R --

rcat | Random generation for categorical distribution
rdirichlet_mat | Random generation for multiple Dirichlet distributions
rmst_weibullNMA | Parameterization of the Weibull distribution for network meta-analysis
rng_distributions | Random number generation distributions
rpwexp | Random generation for piecewise exponential distribution
rweibullNMA | Parameterization of the Weibull distribution for network meta-analysis

## -- S --

set_labels | Set value labels
sim_costs | Expected values from state probabilities
sim_ev | Expected values from state probabilities
sim_ev.stateprobs | Expected values from state probabilities
sim_qalys | Expected values from state probabilities
sim_stateprobs | Simulated state probabilities
sim_stateprobs.survival | Simulate state probabilities from survival curves
stateprobs | State probability object
StateVals | Model for state values
stateval_tbl | Table to store state value parameters
summarize_ce | Summarize costs and effectiveness
summary.ce | Summary method for cost-effectiveness object
summary.eval_rng | Summarize 'eval_rng' object
summary.params | Summarize parameter objects
summary.params_lm | Summarize parameter objects
summary.params_mlogit | Summarize parameter objects
summary.params_mlogit_list | Summarize parameter objects
summary.params_surv | Summarize parameter objects
summary.params_surv_list | Summarize parameter objects
summary.tparams_mean | Summarize 'tparams_mean' object
summary.tparams_transprobs | Summarize 'tparams_transprobs' object
summary.tpmatrix | Summarize transition probability matrix
survival | Survival object
surv_quantile | Survival quantiles

## -- T --

time_intervals | Time intervals
tparams | Transformed parameter object
tparams_mean | Predicted means
tparams_transprobs | Transition probabilities
tparams_transprobs.array | Transition probabilities
tparams_transprobs.data.frame | Transition probabilities
tparams_transprobs.data.table | Transition probabilities
tparams_transprobs.tpmatrix | Transition probabilities
tpmatrix | Transition probability matrix
tpmatrix_id | Transition probability matrix IDs
tpmatrix_names | Names for elements of a transition probability matrix

## -- U --

uniform_rng | Random number generation distributions

## -- W --

weibullNMA | Parameterization of the Weibull distribution for network meta-analysis