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A Bayesian Hierarchical Model that Controls for Non-Adherence in Mobile Menstrual Cycle Tracking

v0.2.0 · Sep 9, 2025 · MIT + file LICENSE

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>.

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r-devel-windows-x86_64 OK
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Check History

OK 13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Jun 9, 2026
WARNING 12 OK · 0 NOTE · 1 WARNING · 0 ERROR · 0 FAILURE Jun 8, 2026
WARNING r-devel-linux-x86_64-debian-gcc

Rd files

Warning in file() :
  cannot open file '/tmp/RtmpbYS7lx/Rf2352504cb2382d': No space left on device
Error in file() : cannot open the connection
Calls: <Anonymous> ... initialRdMacros -> loadRdMacros -> parse_Rd -> file
Execution halted
OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies doParallel foreach genMCMCDiag (>= 0.2.0) ggplot2 ggtext glmnet (>= 4.1.0) gridExtra LaplacesDemon lifecycle mvtnorm optimg parallel (>= 4.0.0) skipTrack

Version History

4 tracked
new 0.2.0 Mar 10, 2026
updated 0.2.0 ← 0.1.2 diff Sep 9, 2025
updated 0.1.2 ← 0.1.0 diff Jan 26, 2025
new 0.1.0 May 15, 2024