Bayesian Distributed Lag Non-Linear Models (B-DLNM).

bdlnm

The goal of bdlnm is to provide tools for fitting Bayesian distributed lag non-linear models (B-DLNM) using the INLA framework. The package allows users to estimate exposure-lag-response associations, generate posterior predictions, compute attributable risk measures, and estimate optimal exposure values within a fully Bayesian framework.

Key features

The package provides functions to:

• Fit Bayesian distributed lag linear and non-linear models using INLA
• Generate predictions of exposure-lag-response associations
• Estimate attributable fractions and attributable numbers
• Estimate optimal exposure values (e.g., minimum risk exposure)
• Visualize exposure–lag–response associations

More detailed examples and tutorials are available in the package vignettes.

Installation

You can install the development version of bdlnm like so:

devtools::install_github("pasahe/bdlnm")

At least the stable version of INLA 23.4.24 (or newest) must be installed beforehand. You can install the newest stable INLA version by:

install.packages("INLA", repos=c(getOption("repos"), INLA="https://inla.r-inla-download.org/R/stable"), dep=TRUE)

Citation

If you use bdlnm in your research, please cite:

citation("bdlnm")

Acknowledgements

This package extends the distributed lag modelling framework implemented in the dlnm package developed by Gasparrini (2011) to a Bayesian setting.