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pacheck

The goal of pacheck is to provide a suite of functions to investigate the probabilistic analysis results of a health economic model.

Installation

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("Xa4P/pacheck")

You can install the version on CRAN using:

install.packages("pacheck")

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Version

Install

install.packages('pacheck')

Version

0.2.2

License

GPL (>= 3)

Issues

1

Pull Requests

0

Stars

5

Forks

0

Maintainer

Xavier Pouwels

Last Published

January 18th, 2026

Functions in pacheck (0.2.2)

df_iviRA_pa

Dataframe of inputs and outputs of a health economic model developed and evaluated with the iviRA R package for testing
check_sum_vars

Check sum variables
do_discount_check

Perform discounted and undiscounted results check
check_mean_qol

Check mean quality of life
calculate_nb

Calculate NMB and NHB for two strategies.
df_ckd_results

A dataframe containing probabilistic outputs for testing
df_ckd_inputs

A dataframe containing probabilistic inputs for testing
do_quick_check

Perform quick checks of inputs and outputs
df_pa_psm

Dataframe for testing
do_check

Perform a check
fit_dist

Fit distribution to parameter
fit_rf_metamodel

Fit random forest metamodel
estimate_decision_sensitivity

Estimate decision sensitivy DSA using linear metamodel
generate_cor

Generate correlation matrix
df_pa

Dataframe for testing
plot_ice

Plotting the incremental cost-effectiveness plane.
perform_simulation_psm

Perform the health economic simulation using partitioned survival model.
fit_lasso_metamodel

Fit LASSO metamodel
perform_dowsa

Perform deterministic one-way sensitivity analyses using probabilistic inputs and outputs.
check_surv_mod

Check parametric survival models
perform_simulation

Perform the health economic simulation.
fit_lm_metamodel

Fit linear metamodel
generate_pa_inputs_psm

Generate probabilistic model inputs for partitioned survival model.
plot_ce

Plotting cost-effectiveness plane for two strategies.
generate_sum_stats

Generate summary statistics
l_psa_aaa

A dataframe containing probabilistic inputs for testing
generate_det_inputs

Generate deterministic model inputs.
generate_pa_inputs

Generate probabilistic model inputs.
plot_nb

Plot (i)NMB or (i)NHB.
plot_ce_mult

Plotting cost-effectiveness plane.
summary_ice

Summary statistics of the incremental cost-effectiveness plane.
plot_ceac

Plotting the cost-effectiveness acceptability curves.
predict_metamodel

Predict using a fitted metamodel
plot_convergence

Plot moving average
vis_1_param

Visualise the distribution of a single parameter
validate_metamodel

Validate metamodels
vis_2_params

Visualise the distribution of two parameters
plot_nb_mult

Plot NMB or NHB.
plot_surv_mod

Plot parametric survival models
check_positive

Check whether variables are strictly positive
check_range

Check range
check_sum_probs

Check sum probabilities
calculate_ceac_mult

Calculate cost-effectiveness probabilities.
calculate_ceac

Calculate cost-effectiveness probabilities for two strategies.
check_binary

Check binary
check_psa_darth

Check PSA inputs & outputs
calculate_nb_mult

Calculate NMB and NHB.