dlim-package: Distributed Lag Interaction Model (DLIM)

In dlim: Distributed Lag Interaction Model

Distributed Lag Interaction Model (DLIM)

Description

The package dlim contains functions to fit, perform inference and estimation on, and visualize a distributed lag interaction model (DLIM).

Modelling framework

A distributed lag interaction model (DLIM) is an extension of a distributed lag model. A DLIM regresses an outcome onto repeated measures of an exposure and allows for associations to vary by a single continuous modifier. More details on methodology are provided in the reference listed below.

Functions and data included in the package

To fit a DLIM using this package, use the dlim function, which calls the cross_basis function to create the cross-basis and estimates regression coefficients using gam from mgcv package.

The predict.dlim S3 function provides point-wise or cumulative effect estimates and uncertainty measures.

The plot_DLF and plot_cumulative functions provide plots of the modified distributed lag functions and the cumulative effect estimate curve.

Additional information

Additonal details on the package dlim are available in the vignette, available by typing:

vignette("dlimOverview")

The dlim package is available on the Comprehensive R Archive Network (CRAN). A development website is available on GitHub (github.com/ddemateis/dlim).

Please use citation("dlim") to cite this package.

Author(s)

Danielle Demateis, Kayleigh Keller, and Ander Wilson

Maintainer: Danielle Demateis <[e-mail]>

References

Demateis et al. (2024) <doi:10.1002/env.2843>, avaibable at (arxiv.org/abs/2401.02939).

See Also

Type 'vignette(dlimOverview)' for a detailed description.

dlim documentation built on May 29, 2024, 8:32 a.m.