skipTrack-package {skipTrack} | R Documentation |
skipTrack: A Bayesian Hierarchical Model that Controls for Non-Adherence in Mobile Menstrual Cycle Tracking
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.
Author(s)
Maintainer: Luke Duttweiler lduttweiler@hsph.harvard.edu (ORCID) [copyright holder]
See Also
Useful links:
Report bugs at https://github.com/LukeDuttweiler/skipTrack/issues
[Package skipTrack version 0.1.0 Index]