Ivan Jacob Agaloos Pesigan 2025-04-10
Research compendium for the manuscript Pesigan, I. J. A., Russell, M. A., Chow, S.-M. (Under Review). Inferences and Effect Sizes for Direct, Indirect, and Total Effects in Continuous-Time Mediation Models. https://doi.org/10.0000/0000000000
This research was made possible by the Prevention and Methodology Training Program (PAMT) funded by a T32 training grant (T32 DA017629 MPIs: J. Maggs & S. Lanza) from the National Institute on Drug Abuse (NIDA), the National Institutes of Health Intensive Longitudinal Health Behavior Cooperative Agreement Program U24AA027684, National Science Foundation grants DUE-2417294, the National Center for Advancing Translational Sciences under UL1TR002014-06, and the National Institute of Diabetes, Digestive & Kidney Diseases under U01DK135126.
Computations for this research were performed on the Pennsylvania State
University’s Institute for Computational and Data Sciences’ Roar
supercomputer. See .sim/README.md and the scripts in the .sim folder
in the GitHub repository for
more details on how the simulations were performed.
You can install manCTMed from
GitHub with:
if (!require("remotes")) install.packages("remotes")
remotes::install_github("jeksterslab/manCTMed")Standard errors and confidence intervals for the direct, indirect, and
total effects for continuous-time mediation models as well as
visualization tools are available in the cTMed package. Documentation
and examples can be found in the accompanying website
(https://jeksterslab.github.io/cTMed).
See GitHub Pages for package documentation.