Package: BayesianReasoning 0.4.2.9000
BayesianReasoning: Plot Positive and Negative Predictive Values for Medical Tests
Functions to plot and help understand positive and negative predictive values (PPV and NPV), and their relationship with sensitivity, specificity, and prevalence. See Akobeng, A.K. (2007) <doi:10.1111/j.1651-2227.2006.00180.x> for a theoretical overview of the technical concepts and Navarrete et al. (2015) for a practical explanation about the importance of their understanding <doi:10.3389/fpsyg.2015.01327>.
Authors:
BayesianReasoning_0.4.2.9000.tar.gz
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BayesianReasoning.pdf |BayesianReasoning.html✨
BayesianReasoning/json (API)
NEWS
| # Install 'BayesianReasoning' in R: |
| install.packages('BayesianReasoning', repos = c('https://gorkang.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/gorkang/bayesianreasoning/issues
bayesian-inferencenegative-predictive-valuepositive-predictive-value
Last updated 8 months agofrom:f382c4a004. Checks:OK: 1 ERROR: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 08 2024 |
| R-4.5-win | ERROR | Nov 08 2024 |
| R-4.5-linux | ERROR | Nov 08 2024 |
| R-4.4-win | ERROR | Nov 08 2024 |
| R-4.4-mac | ERROR | Nov 08 2024 |
| R-4.3-win | ERROR | Nov 08 2024 |
| R-4.3-mac | ERROR | Nov 08 2024 |
Exports:%>%min_possible_prevalenceplot_cutoffPPV_diagnostic_vs_screeningPPV_heatmapremove_layers_cutoff_plot
Dependencies:base64encbigDbitopsbslibcachemclicolorspacecommonmarkcpp11curldigestdplyrevaluatefansifarverfastmapfontawesomefsgenericsggforceggplot2ggtextgluegridtextgtgtablehighrhtmltoolshtmlwidgetsisobandjpegjquerylibjsonlitejuicyjuiceknitrlabelinglatticelifecyclemagrittrmarkdownMASSMatrixmemoisemgcvmimemunsellnlmepillarpkgconfigplyrpngpolyclippurrrR6rappdirsRColorBrewerRcppRcppEigenreactablereactRreshape2rlangrmarkdownsassscalesstringistringrsystemfontstibbletidyrtidyselecttinytextweenrutf8V8vctrsviridisLitewithrxfunxml2yaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Show minimum possible prevalence given the test characteristics | min_possible_prevalence |
| plot_cutoff Create a cutoff plot, showing the healthy and sick distributions, and the consequences of different cutoff points | plot_cutoff |
| Plot PPV values for a diagnostic and a screening group | PPV_diagnostic_vs_screening |
| Plot PPV and NPV heatmaps | PPV_heatmap |
| remove_layers_cutoff_plot Remove layers from a cutoff plot. This is useful to show how different things are calculated (e.g. Sensitivity) | remove_layers_cutoff_plot |
