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skipTrack  

A Bayesian Hierarchical Model that Controls for Non-Adherence in Mobile Menstrual Cycle Tracking
View on CRAN: Click here


Download and install skipTrack package within the R console
Install from CRAN:
install.packages("skipTrack")

Install from Github:
library("remotes")
install_github("cran/skipTrack")

Install by package version:
library("remotes")
install_version("skipTrack", "0.2.0")



Attach the package and use:
library("skipTrack")
Maintained by
Luke Duttweiler
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-05-16
Latest Update: 2025-01-27
Description:
Implements a Bayesian hierarchical model designed to identify skips in mobile menstrual cycle self-tracking on mobile apps. Future developments will allow for the inclusion of covariates affecting cycle mean and regularity, as well as extra information regarding tracking non-adherence. Main methods to be outlined in a forthcoming paper, with alternative models from Li et al. (2022) <doi:10.1093/jamia/ocab182>.
How to cite:
Luke Duttweiler (2024). skipTrack: A Bayesian Hierarchical Model that Controls for Non-Adherence in Mobile Menstrual Cycle Tracking. R package version 0.2.0, https://cran.r-project.org/web/packages/skipTrack. Accessed 06 Mar. 2026.
Previous versions and publish date:
0.1.0 (2024-05-16 16:10), 0.1.2 (2025-01-27 22:50)
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Full skipTrack package functions and examples
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