Introduction to BayesianReasoning

Gorka Navarrete

2021-06-17

Bayesian reasoning in medical contexts

This package includes a few functions to plot and help understand Positive and Negative Predictive Values, and their relationship with Sensitivity, Specificity and Prevalence.

The BayesianReasoning package has three main functions:


If you want to install the package can use: remotes::install_github("gorkang/BayesianReasoning"). Please report any problems you find in the Issues Github page.

There is a shiny app implementation with most of the main features available.


PPV_heatmap()

Plot heatmaps with PPV or NPV values for a given specificity and a range of Prevalences and FP or FN (1 - Sensitivity). The basic parameters are:


PPV_heatmap(Min_Prevalence = 1,
            Max_Prevalence = 1000, 
            Sensitivity = 100, 
            Max_FP = 2, 
            Language = "en")


NPV

You can also plot an NPV heatmap with PPV_NPV = “NPV”.


PPV_heatmap(PPV_NPV = "NPV",
            Min_Prevalence = 800,
            Max_Prevalence = 1000, 
            Sensitivity = 80, 
            Max_FP = 5, 
            Language = "en")