Package: TwoCutoff 0.1.0

TwoCutoff: Deriving Clinically Interpretable Cutoffs for Disease Biomarkers
Provides a reproducible pipeline for deriving two clinically meaningful cutoffs for disease biomarkers using a unified two-stage framework. The package integrates finite mixture modeling with risk prediction using biomarker plus clinical features, followed by decision curve analysis to evaluate clinical utility. Outputs include biomarker density plots, risk calibration curves, decision curves, and summary tables of diagnostic performance. Designed for researchers in bio-statistics, neurology, and data science, this package emphasizes reproducibility, transparency, and clear clinical relevance.
Authors:
TwoCutoff_0.1.0.tar.gz
TwoCutoff_0.1.0.tar.gz(r-4.7-any)TwoCutoff_0.1.0.tar.gz(r-4.6-any)
TwoCutoff_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
TwoCutoff/json (API)
| # Install 'TwoCutoff' in R: |
| install.packages('TwoCutoff', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- alzheimer_data - Alzheimer’s Biomarker Dataset
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:46a709ed0e. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 214 | ||
| source / vignettes | OK | 231 | ||
| linux-release-x86_64 | OK | 208 | ||
| wasm-release | OK | 198 |
Exports:adjust_scorecompare_performancedca_analysisderive_cutoffs_percentilederive_cutoffs_sensspecevaluate_performanceplot_two_cutoff
Dependencies:askpassbase64encbslibcachemcaretclasscliclockcodetoolscpp11crosstalkcurldata.tablediagramdigestdplyre1071evaluatefarverfastmapfontawesomeforeachfsfuturefuture.applygenericsggplot2globalsgluegowergridExtragtablehardhathighrhtmltoolshtmlwidgetshttripredisobanditeratorsjquerylibjsonlitekernlabKernSmoothknitrlabelinglaterlatticelavalazyevallifecyclelistenvlubridatemagrittrMASSMatrixmemoisemimemixtoolsModelMetricsnlmennetnumDerivopensslotelparallellypatchworkpillarpkgconfigplotlyplyrpROCprodlimprogressrpromisesproxypurrrR6rappdirsRColorBrewerRcpprecipesreshape2rlangrmarkdownrpartS7sassscalessegmentedshapesparsevctrsSQUAREMstringistringrsurvivalsystibbletidyrtidyselecttimechangetimeDatetinytextzdbutf8vctrsviridisLitewithrxfunxgboostyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Adjust biomarker score with confounder-adjusted risk model | adjust_score |
| Alzheimer’s Biomarker Dataset | alzheimer_data |
| Compare cutoff methods | compare_performance |
| Decision Curve Analysis (DCA) | dca_analysis |
| Derive percentile-based biomarker cutoffs using adjusted risk | derive_cutoffs_percentile |
| Derive ROC-based biomarker cutoffs using adjusted risk | derive_cutoffs_sensspec |
| Evaluate classification performance | evaluate_performance |
| Plot two-cutoff classification | plot_two_cutoff |
| Print method for derive_cutoffs_percentile objects | print.cutoff.percentile |
| Print method for derive_cutoffs_sensspec objects | print.cutoff.sensspec |
| Print Method for twocutoff.adjscore Objects | print.twocutoff.adjscore |
