https://phmcc.r-universe.devRecent package updates in phmccR-universehttps://github.com/phmcc.pnghttps://phmcc.r-universe.devFri, 19 Jun 2026 07:22:58 GMTpaulhmcclelland@protonmail.com (Paul Hsin-ti McClelland)Build EQUATOR-style flowcharts for clinical studies by sequentially defining inclusion and exclusion criteria, study arms, and endpoints. The pipe-friendly API supports CONSORT (randomized trials), STROBE (observational cohorts), STARD (diagnostic accuracy), PRISMA (systematic reviews), and MOOSE (observational meta-analysis) diagram layouts, as well as multi-source convergence, split-and-recombine, factorial, and hybrid topologies. Diagrams are rendered via 'grid' graphics in both data-driven (automatic counting) and manual-count modes, with optional 'DiagrammeR'/'Graphviz' output.https://github.com/r-universe/phmcc/actions/runs/28158398545Fri, 19 Jun 2026 07:22:58 GMTselecta0.6.0successhttps://phmcc.r-universe.devhttps://github.com/phmcc/selectaadvanced_workflows.Rmdadvanced_workflows.htmlAdvanced Workflows2026-06-18 02:48:562026-06-19 07:22:58enrollment_diagrams.Rmdenrollment_diagrams.htmlEnrollment Diagrams2026-06-18 02:48:562026-06-19 07:22:58graphviz_export.Rmdgraphviz_export.htmlGraphviz Export2026-06-18 02:48:562026-06-19 07:22:58split_recombine.Rmdsplit_recombine.htmlSplit-and-Recombine Diagrams2026-06-18 02:48:562026-06-19 07:22:58systematic_reviews.Rmdsystematic_reviews.htmlSystematic Reviews2026-06-18 02:48:562026-06-19 07:22:58paulhmcclelland@protonmail.com (Paul Hsin-ti McClelland)A comprehensive framework for descriptive statistics and regression analysis that produces publication-ready tables and forest plots. Provides a unified interface from descriptive statistics through multivariable modeling, with support for linear models, generalized linear models, Cox proportional hazards, and mixed-effects models. Also includes univariable screening, multivariate regression, model comparison, and export to multiple formats including PDF, DOCX, PPTX, 'LaTeX', HTML, and RTF. Built on 'data.table' for computational efficiency.https://github.com/r-universe/phmcc/actions/runs/27090323375Thu, 07 May 2026 00:49:37 GMTsummata0.11.5successhttps://phmcc.r-universe.devhttps://github.com/phmcc/summataadvanced_workflows.Rmdadvanced_workflows.htmlAdvanced Workflows2026-01-12 21:15:152026-03-03 04:07:30descriptive_tables.Rmddescriptive_tables.htmlDescriptive Tables2026-01-12 21:15:152026-03-03 04:07:30forest_plots.Rmdforest_plots.htmlForest Plots2026-01-12 21:15:152026-03-03 04:07:30installation_setup.Rmdinstallation_setup.htmlInstallation and Setup2026-02-16 03:09:502026-03-14 21:29:37model_comparison.Rmdmodel_comparison.htmlModel Comparison2026-01-12 21:15:152026-03-03 04:07:30multivariate_regression.Rmdmultivariate_regression.htmlMultivariate Regression2026-02-16 03:09:502026-03-03 04:07:30regression_modeling.Rmdregression_modeling.htmlRegression Modeling2026-01-12 21:15:152026-03-14 21:29:37survival_tables.Rmdsurvival_tables.htmlSurvival Tables2026-01-12 21:15:152026-03-03 04:07:30table_export.Rmdtable_export.htmlTable Export2026-01-12 21:15:152026-03-03 04:07:30