Learn R Programming

⚠️There's a newer version (1.1.0) of this package.Take me there.

heemod - Health Economic Evaluation MODelling

heemod is an R toolset for health economic evaluation modelling. It aims to provide a simple and consistent interface for Markov models specification and comparison (for decision trees or cohort simulation). Non-homogeneous Markov models (with time varying properties) are supported.

Most of the analyses presented in Decision Modelling for Health Economic Evaluation can be performed with heemod. See vignette("i-reproduction", "heemod") for an exact reproduction of the analyses from the book.

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")

Main features

Graphical user interface with shiny.
Time-varying transition probabilities.
Time-varying values attached to states.
Microsimulation-like models.
Probabilistic uncertainty analysis (PSA).
Covariance analysis for PSA.
Deterministic sensitivity analysis (DSA).
Multiple state membership correction methods (life-table, half-cycle, etc.).
Demographic analysis to compute population-level results.
Heterogeneity analysis.
Parallel computing support.

Learning heemod

To get started read the introduction in vignette("a-introduction", "heemod"). Time-varying probabilities and values are explained in vignette("b-time-dependency", "heemod").

Specific analysis examples (mostly inspired from Decision Modelling for Health Economic Evaluation) can be found in the following vignettes:

Homogeneous Markov model in vignette("c-homogeneous", "heemod").
Non-homogeneous Markov model in vignette("d-non-homogeneous", "heemod").
Probabilistic uncertainty analysis in vignette("e-probabilistic", "heemod").
Deterministic sensitivity analysis in vignette("f-sensitivity", "heemod").
Heterogeneity & Demographic analysis in vignette("g-heterogeneity", "heemod").
Running the models from tabular inputs in vignette("h-tabular", "heemod").

Devs

Kevin Zarca and Antoine Filipović-Pierucci.

Contributors

Copy Link

Version

Install

install.packages('heemod')

Monthly Downloads

1,092

Version

0.7.1

License

GPL (>= 3)

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/pierucci/heemod

Homepage

https://pierucci.org

Maintainer

Antoine FilipovicPierucci

Last Published

November 29th, 2016

Functions in heemod (0.7.1)

acceptability_curve

Acceptability Curve from Probabilistic Analysis

create_demographic_table

Read a Demographic Table

create_df_from_tabular

Load Data From a Folder Into an Environment

Compute State Values per Cycle

create_model_from_tabular

Create a heemod Model From Tabular Files Info

create_model_list_from_tabular

Read Models Specified by Files

create_parameters_from_tabular

Create a Parameter Definition From Tabular Input

create_matrix_from_tabular

Create a Transition Matrix From Tabular Input

create_options_from_tabular

Create Model Options From a Tabular Input

create_states_from_tabular

Create State Definitions From Tabular Input

define_sensitivity

Define a Sensitivity Analysis

Define a Markov Model State

define_correlation

Define a Correlation Structure for Probabilistic Uncertainty Analysis

Define a Markov Model

define_multinom

Define That Parameters Belong to the Same Multinomial Distribution

Define Parameters Distribution for Probabilistic Analysis

define_state_list

Define Markov Model State List

Define Transition Matrix for Markov Model

define_parameters

Define Markov Model Parameters

Probability Density Functions for Probabilistic Uncertainty Analysis

Hack to Work Around a Discounting Issue

Expand Time-Dependant States into Tunnel States

Evaluate Strategy

eval_state_list

Evaluate Markov Model States

Discount a Quantity Over Time

gather_model_info

Gather Information for Running a Model From Tabular Data

eval_strategy_newdata

Iteratively Evaluate a Markov Model With New Parameter Values

Display the Code to Generate an Object

Interpolate Lazy Dots

Check Wholenumbers

Evaluate Markov Model Transition Matrix

get_counts.updated_model

Get State Membership Counts

eval_models_from_tabular

Evaluate Models From a Tabular Source

scale.combined_model

Normalize Cost and Effect

get_values.updated_model

Get Strategy Values

Return Efficiency Frontier

get_state_names

Get State Names

get_parameter_names

Return parameters names

heemod: Health Economic Evaluation MODelling

Insert Elements in Vector

Run Model on New Data

Make Syntactically Valid Names

Use WHO Mortality Rate

Evaluate Resampling Definition

eval_parameters

Evaluate Markov model parameters

get_state_number

Return Number of State

get_state_value_names

Return Names of State Values

Returns "s" if x > 1

Convenience Functions to Compute Probabilities

run_probabilistic

Run Probabilistic Uncertainty Analysis

Read the accepted file formats for tabular input

safe-conversion

Safely Convert From Characters to Numbers

run_sensitivity

Run Sensitivity Analysis

Run one or more Markov Model

run_model_tabular

Run Analyses From Files

Check File Type

Remove Blank Rows From Table

Plot Results of Probabilistic Analysis

Plot Results of a Markov Model

Weighted Summary

get_matrix_order

Return Markov Model Transition Matrix Order

Get Markov Model Transition Matrix

Look Up Values in a Data Frame

Check if All the Elements of a List Are the Same

parse_multi_spec

Specify Inputs for Multiple Models From a Single File

Plot Sensitivity Analysis

Save Model Outputs

summary.run_model

Summarise Markov Model Results

Combine Multiple Models

Check Markov Model Transition Matrix

Convert Lazy Dots to Expression List

Run heemod on a Cluster

Convert Data Frame Factor Variables to Character

Compute Count of Individual in Each State per Cycle

check_strategy_index

Check Strategy Index

Check Model States for Consistency