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heemod - Health Economic Evaluation MODelling

Markov Models for Health Economic Evaluations. An implementation of the modelling and reporting features described in reference textbooks and guidelines: deterministic and probabilistic sensitivity analysis, heterogeneity analysis, time dependency on state-time and model-time (semi-Markov and non-homogeneous Markov models), etc.

You can install:

the latest released version from CRAN with:

install.packages("heemod")

the latest development version from github with:

devtools::install_github("aphp/heemod")

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

Features

Main features:

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, custom method, etc.).
Demographic analysis to compute population-level results.
Heterogeneity analysis.
Parallel computing support.
Features for budget impact analysis.
Interface with SAVI and BCEA.

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

0.16.0

License

GPL (>= 3)

Maintainer

Kevin Zarca

Last Published

July 18th, 2023

Functions in heemod (0.16.0)

Apply a time shift to a survival distribution

Apply an Acceleration Factor

Combine Probabilities

Apply a Hazard Ratio

Compute Count of Individual in Each State per Cycle

check_strategy_index

Check Strategy Index

Compute State Values per Cycle

construct_part_surv_tib

construct a survival object from tabular specification

calibrate_model

Calibrate Model Parameters

create_model_list_from_tabular

Read Models Specified by Files

Convert Lazy Dots to Expression List

Define a Markov Model State

Convert Data Frame Factor Variables to Character

Run heemod on a Cluster

calc_prob_from_surv

Calculate Probability of Event

Combine Multiple Models

define_starting_values

Define Starting State Values

Discount a Quantity Over Time. Should be a scalar if time is specified, a vector otherwise

create_options_from_tabular

Create Model Options From a Tabular Input

define_part_surv

Define Partitioned Survival

Evaluate Survival Distributions

define_transition

Define Transition Matrix for Markov Model

check_cycle_inputs

Check Cycle and Time Inputs

Check Model States for Consistency

define_calibration_fn

Define Calibration Function

Remove Blank Rows From Table

create_df_from_tabular

Load Data From a Folder Into an Environment

Define Parameters Distribution for Probabilistic Analysis

expand_if_necessary

Expand States and Transition

dispatch_strategy

Dispatch Values According to Strategy

define_strategy

Define a Markov Model

Check Markov Model Transition Matrix

define_state_list

Define Markov Model State List

get_parameter_names

Return parameters names

Return Efficiency Frontier

Define a Sensitivity Analysis

Expand Time-Dependant States into Tunnel States

define_correlation

Define a Correlation Structure for Probabilistic Uncertainty Analysis

Export PSA Results for SAVI

define_survival

Define a Survival Distribution

create_matrix_from_tabular

Create a Transition Matrix From Tabular Input

define_surv_table

Define a survival distribution based on explicit survival probabilities

create_model_from_tabular

Create a heemod Model From Tabular Files Info

run_model_tabular

Run Analyses From Files

create_demographic_table

Read a Demographic Table

Get count number

load_surv_models

Load a set of survival fits

Evaluate Survival Distributions

Read the accepted file formats for tabular input

Run Markov Model

get_counts.updated_model

Get State Membership Counts

Look Up Values in a Data Frame

Evaluate Resampling Definition

eval_strategy_newdata

Iteratively Evaluate a Markov Model With New Parameter Values

Define Initial Counts

create_parameters_from_tabular

Create a Parameter Definition From Tabular Input

Define Inflow for a BIA

eval_parameters

Evaluate Markov model parameters

Plot general survival models

Get Markov Model Transition Matrix

create_states_from_tabular

Create State Definitions From Tabular Input

Probability Density Functions for Probabilistic Uncertainty Analysis

Set Covariates of a Survival Distribution

scale.combined_model

Normalize Cost and Effect

gather_model_info

Gather Information for Running a Model From Tabular Data

define_parameters

Define Markov Model Parameters

Run Probabilistic Uncertainty Analysis

eval_models_from_tabular

Evaluate Models From a Tabular Source

Project Beyond a Survival Distribution with Another

safe_conversion

Safely Convert From Characters to Numbers

Make Syntactically Valid Names

Markov Models for Health Economic Evaluations

Evaluate Strategy

define_spline_survival

Define a Restricted Cubic Spline Survival Distribution

Use the BCEA package

extract_stratum

Extract Product-Limit Table for a Stratum

Hack to Work Around a Discounting Issue

dispatch_strategy_hack

Hack to Automate Use of Strategy Name

Interpolate Quosures

Mix Two or More Survival Distributions

get_counts_diff

Get count matrix and difference between two cycles

eval_state_list

Evaluate Markov Model States

get_state_value_names

Return Names of State Values

Check File Type

get_matrix_order

Return Markov Model Transition Matrix Order

summary.run_model

Summarise Markov Model Results

get_values.updated_model

Get Strategy Values

Extract Evaluated Parameters

Save Model Outputs

part_survs_from_surv_inputs

Convert saved fits to partitioned survival objects

eval_transition

Evaluate Markov Model Transition Matrix

Extract Product-Limit Tables

get_state_names

Get State Names

Returns "s" if x > 1

get_state_number

Return Number of State

reindent_transition

Reindent Transition Matrix

Objects exported from other packages

Check if All the Elements of a List Are the Same

Plot Sensitivity Analysis

Project Beyond a Survival Distribution with Another (pairwise)

Convenience Functions to Compute Probabilities

Check Wholenumbers

rescale_discount_rate

Rescale Discount Rate

Run Model on New Data

summary.surv_shift

Summarize surv_shift objects

Insert Elements in Vector

parse_multi_spec

Specify Inputs for Multiple Models From a Single File

Run Sensitivity Analysis

Weighted Summary

Plot Results of Probabilistic Analysis

Plot Results of a Markov Model

Use WHO Mortality Rate

calc_surv_from_prob

Calculate Probability of Survival

Apply an Odds Ratio

acceptability_curve

Acceptability Curve from Probabilistic Analysis