Ivan Jacob Agaloos Pesigan 2025-10-02
Research compendium for the manuscript Pesigan, I. J. A., Russell, M. A., Chow, S.-M. (2025). Common and Unique Latent Transition Analysis (CULTA) as a Way to Examine the Trait-State Dynamics of Alcohol Intoxication. Psychology of Addictive Behaviors 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 Center for Advancing Translational Sciences grant UL1TR002014-06; and pilot mentoring and professional development awards through P50DA039838 awarded to Michael A. Russell (National Institute on Drug Abuse, PI: L. Collins), as well as support from the Social Science Research Institute at Penn State and departmental funds awarded to Michael A. Russell.
Computations for this research were performed on the Pennsylvania State
University’s Institute for Computational and Data Sciences’ Roar
supercomputer using SLURM for job scheduling (Yoo et al., 2003), GNU
Parallel to run the simulations in parallel (Tange, 2021), and Apptainer
to ensure a reproducible software stack (Kurtzer et al., 2017, 2021).
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 manCULTA from
GitHub with:
if (!require("remotes")) install.packages("remotes")
remotes::install_github("jeksterslab/manCULTA")See Containers for containerized versions of the package.
See https://github.com/jeksterslab/manCULTA/blob/main/.setup/latex/manCULTA-manuscript.Rtex for the latex file of the manuscript. See https://github.com/jeksterslab/manCULTA/blob/latex/manCULTA-manuscript.pdf for the compiled PDF.
See GitHub Pages for package documentation.