A set of independent pvalues can be modeled as draws from a mixture of beta distributions. This package provides tools to estmate such a mixture given some data. One component of the mixture is necessarily uniform, representing pvalues corresponding to true null hypotheses. The nonuniform components of the mixture represent tests where the alternative hypothesis is true. Using the method described by Allison et al. (2002), pvalues are converted to Bayesian posterior probabilities using mixture models and Bayes' rule. This Bayesian posterior probability can be interpreted as the probability that the alternative hypothesis is true. These probabilities can be combined using the standard rules of probability to perform composite hypothesis tests, as described by Erikson, Kim, and Allison (2010).
Package details 


Maintainer  
License  MIT 
Version  0.1.0 
Package repository  View on GitHub 
Installation 
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