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BayesianReasoning
View on CRAN: Click
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Download and install BayesianReasoning package within the R console
Install from CRAN:
install.packages("BayesianReasoning")
Install from Github:
library("remotes")
install_github("cran/BayesianReasoning")
Install by package version:
library("remotes")
install_version("BayesianReasoning", "0.4.2")
Attach the package and use:
library("BayesianReasoning")
Maintained by
Gorka Navarrete
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-06-30
Latest Update: 2022-01-07
Description:
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)
for a theoretical overview of
the technical concepts and Navarrete et al. (2015) for a practical
explanation about the importance of their understanding
.
How to cite:
Gorka Navarrete (2020). BayesianReasoning: Plot Positive and Negative Predictive Values for Medical Tests. R package version 0.4.2, https://cran.r-project.org/web/packages/BayesianReasoning. Accessed 21 Nov. 2024.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for BayesianReasoning
Functions, R codes and Examples using
the BayesianReasoning R package
Some associated functions: BayesianReasoning-package . BayesianReasoning . PPV_diagnostic_vs_screening . PPV_heatmap . min_possible_prevalence . pipe . plot_cutoff . remove_layers_cutoff_plot .
Some associated R codes: BayesianReasoning-package.R . BayesianReasoning.R . PPV_diagnostic_vs_screening.R . PPV_heatmap.R . globals.R . helper_functions.R . min_possible_prevalence.R . plot_cutoff.R . Full BayesianReasoning package functions and examples
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