skipTrack
0.2.0A Bayesian Hierarchical Model that Controls for Non-Adherence in Mobile Menstrual Cycle Tracking
Overview
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.
New Features
*skipTrack.fit() can now incorporate longitudinal data in X matrix. Users are no
longer limited to one row of data per individual in X, but can now have one row
of data per cycle if desired.
Minor improvements and fixes
*skipTrack.results() now produces a helpful error message if burnIn is less than fit length.
*Fit now sets all starting cij values to 1 which is much more logical and mixing occurs
much quicker.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-04
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- WARNING12 OK, 1 WARNING2026-06-08
- OK14 OK2026-03-10
Documentation
- Help pages
- 30 (1 internal)includes a package overview page
- Examples that run
- 100%9 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 98%
- Return-value docs
- 100%
- Help pages citing references
- 17%
Downloads
Repository
- PRs merged (all time)
- not measured
- Median days to close, 50 most recently updated closed issues
- 170
- Median days to close, 50 most recently updated closed PRs
- not measured
Releases over time
Issues over time
7 development-tooling and community-health practices detected across 6 families in the upstream repository
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Dependencies
Code & Tests
People & History
Package metadata
- First published
- 2024-05-16
- Total releases
- 3 / 2 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 470 KB
Cite
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Run in R for the authors' preferred citation:
citation("skipTrack")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
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