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heemod - Health Economic Evaluation MODelling

Health Economic Evaluation Modelling: decision trees and cohort simulations. Provides a simple and consistent interface for Markov models specification, comparison, sensitivity and probabilistic analysis, input of survival models, etc. Models with time varying properties (non-homogeneous Markov models and semi-Markov models) are supported.

You can install:

  • the latest released version from CRAN with:
install.packages("heemod")
  • the latest development version from github with:
devtools::install_github("pierucci/heemod@devel")
  • heemod can be cited with:

Filipović-Pierucci A, Zarca K and Durand-Zaleski I (2017). “Markov Models for Health Economic Evaluation: The R Package heemod.” ArXiv e-prints. R package version 0.8.0, 1702.03252, <URL: https://pierucci.org/heemod>.

Features

Main features:

  • Graphical user interface with shiny.
  • Accounting for time-dependency:
    • For both model time and state time.
    • Time-varying transition probabilities.
    • Time-varying values attached to states.
  • Probabilistic uncertainty analysis (PSA).
    • With correlated resampling.
    • Covariance analysis for PSA.
    • Expected value of perfect information (EVPI).
  • Deterministic sensitivity analysis (DSA).

Other features:

  • Multiple state membership correction methods (life-table, half-cycle, etc.).
  • Demographic analysis to compute population-level results.
  • Heterogeneity analysis.
  • Parallel computing support.
  • Features for budget impact analysis.

Most of the analyses presented in Decision Modelling for Health Economic Evaluation can be performed with heemod. See the Reproducing Exact Results from DMHEE vignette for an exact reproduction of the analyses from the book.

Learning heemod

To get started read the An Introduction to heemod vignette. Specific analysis examples (mostly inspired from Decision Modelling for Health Economic Evaluation) can be found in the package vignettes.

Devs

Kevin Zarca and Antoine Filipović-Pierucci.

Contributors

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Version

Install

install.packages('heemod')

Monthly Downloads

1,092

Version

0.9.0

License

GPL (>= 3)

Issues

44

Pull Requests

0

Stars

41

Forks

25

Maintainer

Antoine FilipovicPierucci

Last Published

April 7th, 2017

Functions in heemod (0.9.0)

apply_af

Apply an Acceleration Factor
apply_hr

Apply a Hazard Ratio
check_states

Check Model States for Consistency
check_strategy_index

Check Strategy Index
calc_prob_from_surv

Calculate Probability of Event
calc_surv_from_prob

Calculate Probability of Survival
calibrate_model

Calibrate Model Parameters
check_cycle_inputs

Check Cycle and Time Inputs
compute_counts

Compute Count of Individual in Each State per Cycle
create_parameters_from_tabular

Create a Parameter Definition From Tabular Input
create_states_from_tabular

Create State Definitions From Tabular Input
compute_icer

Compute ICER
create_matrix_from_tabular

Create a Transition Matrix From Tabular Input
create_model_from_tabular

Create a
define_calibration_fn

Define Calibration Function
discount_hack

Hack to Work Around a Discounting Issue
dispatch_strategy

Dispatch Values According to Strategy
eval_surv

Evaluate Survival Distributions
eval_transition

Evaluate Markov Model Transition Matrix
extract_stratum

Extract Product-Limit Table for a Stratum
is_csv

Check File Type
acceptability_curve

Acceptability Curve from Probabilistic Analysis
add_hazards

Add Hazards
check_matrix

Check Markov Model Transition Matrix
check_names

Check Names
define_correlation

Define a Correlation Structure for Probabilistic
extract_params

Extract Evaluated Parameters
extract_strata

Extract Product-Limit Tables
heemod

heemod: Health Economic Evaluation MODelling
define_psa

Define Parameters Distribution for Probabilistic Analysis
define_spline_survival

Define a Restricted Cubic Spline Survival Distribution
define_transition

Define Transition Matrix for Markov Model
discount

Discount a Quantity Over Time
clean_factors

Convert Data Frame Factor Variables to Character
cluster

Run
create_demographic_table

Read a Demographic Table
create_df_from_tabular

Load Data From a Folder Into an Environment
plot.run_model

Plot Results of a Markov Model
plot.surv_obj

Plot general survival models
reexports

Objects exported from other packages
create_model_list_from_tabular

Read Models Specified by Files
create_options_from_tabular

Create Model Options From a Tabular Input
define_dsa

Define a Sensitivity Analysis
define_inflow

Define Inflow for a BIA
define_init

Define Initial Counts
define_multinom

Define That Parameters Belong to the Same Multinomial
define_strategy

Define a Markov Model
define_survival

Define a Survival Distribution
eval_models_from_tabular

Evaluate Models From a Tabular Source
eval_parameters

Evaluate Markov model parameters
filter_blanks

Remove Blank Rows From Table
gather_model_info

Gather Information for Running a Model From Tabular Data
get_state_number

Return Number of State
eval_strategy

Evaluate Strategy
eval_strategy_newdata

Iteratively Evaluate a Markov Model With New Parameter
get_code

Display the Code to Generate an Object
scale.combined_model

Normalize Cost and Effect
plot.dsa

Plot Sensitivity Analysis
plot.psa

Plot Results of Probabilistic Analysis
run_model_tabular

Run Analyses From Files
rescale_discount_rate

Rescale Discount Rate
get_counts.updated_model

Get State Membership Counts
insert

Insert Elements in Vector
interp_heemod

Interpolate Lazy Dots
is.wholenumber

Check Wholenumbers
define_state

Define a Markov Model State
define_state_list

Define Markov Model State List
eval_resample

Evaluate Resampling Definition
get_state_value_names

Return Names of State Values
modify

Modify Object
parse_multi_spec

Specify Inputs for Multiple Models From a Single File
project_fn

Project Beyond a Survival Distribution with Another
eval_state_list

Evaluate Markov Model States
get_frontier

Return Efficiency Frontier
get_matrix_order

Return Markov Model Transition Matrix Order
get_transition

Get Markov Model Transition Matrix
get_values.updated_model

Get Strategy Values
plur

Returns "s" if x > 1
pool

Pool Two or More Survival Distributions
set_covariates

Set Covariates of a Survival Distribution
summary.run_model

Summarise Markov Model Results
apply_or

Apply an Odds Ratio
list_all_same

Check if All the Elements of a List Are the Same
probability

Convenience Functions to Compute Probabilities
project

Project Beyond a Survival Distribution with Another
wtd_summary

Weighted Summary
run_psa

Run Probabilistic Uncertainty Analysis
as_expr_list

Convert Lazy Dots to Expression List
combine_models

Combine Multiple Models
combine_probs

Combine Probabilities
compute_surv

Evaluate Survival Distributions
compute_values

Compute State Values per Cycle
define_parameters

Define Markov Model Parameters
define_part_surv

Define Partitioned Survival
dispatch_strategy_hack

Hack to Automate Use of Strategy Name
expand_state

Expand Time-Dependant States into Tunnel States
export_savi

Export PSA Results for SAVI
read_file

Read the accepted file formats for tabular input
safe-conversion

Safely Convert From Characters to Numbers
save_outputs

Save Model Outputs
distributions

Probability Density Functions for Probabilistic
get_parameter_names

Return parameters names
get_state_names

Get State Names
look_up

Look Up Values in a Data Frame
make_names

Make Syntactically Valid Names
run_dsa

Run Sensitivity Analysis
run_model

Run Markov Model
update-model

Run Model on New Data
who-mortality

Use WHO Mortality Rate