Package: skipTrack 0.1.1.9000

Luke Duttweiler

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

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>.

Authors:Luke Duttweiler [aut, cre, cph]

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Peer review:

Bug tracker:https://github.com/lukeduttweiler/skiptrack/issues

On CRAN:

5 exports 2.14 score 80 dependencies 4 scripts 139 downloads

Last updated 28 days agofrom:2939faa83d. Checks:OK: 5 NOTE: 2. Indexed: yes.

Exports:skipTrack.diagnosticsskipTrack.fitskipTrack.resultsskipTrack.simulateskipTrack.visualize

Dependencies:briocallrclicodacodetoolscolorspacecommonmarkcrayoncurldescdiffobjdigestdoParallelellipseevaluatefansifarverfftwtoolsforeachfsgenMCMCDiagggplot2ggtextglmnetgluegridExtragridtextgtablehighrisobanditeratorsjpegjsonliteknitrlabelingLaplacesDemonlatticelifecyclemagrittrmarkdownMASSMatrixmcmcsemgcvmunsellmvtnormnlmeoptimgpillarpkgbuildpkgconfigpkgloadpngpraiseprocessxpsR6RColorBrewerRcppRcppArmadilloRcppEigenrematch2rlangrprojrootscalesshapestringistringrsurvivaltestthattibbleucminfutf8vctrsviridisLitewaldowithrxfunxml2yaml