skipTrack-package: skipTrack: A Bayesian Hierarchical Model that Controls for...
In skipTrack: A Bayesian Hierarchical Model that Controls for Non-Adherence in Mobile Menstrual Cycle Tracking
skipTrack-package 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) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1093/jamia/ocab182")}.
Author(s)
Maintainer: Luke Duttweiler lduttweiler@hsph.harvard.edu (ORCID) [copyright holder]
See Also
Useful links:
skipTrack documentation built on April 3, 2025, 6:21 p.m.
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| skipTrack-package | 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) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1093/jamia/ocab182")}.
Author(s)
Maintainer: Luke Duttweiler lduttweiler@hsph.harvard.edu (ORCID) [copyright holder]
See Also
Useful links:
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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