Unbiased Analysis of Today's Healthcare Issues

Addressing Type S vs. Type M errors with Bayesian Hierarchical Modeling

In statistics, most statistical tests aim to trade off type I and type II errors.  Type I error is the incorrect rejection of a true null hypothesis, in other words a false positive.  Type II errors are the incorrect retaining a false null hypothesis; in other words, a false negative.  Oftentimes, the null hypothesis is posed […]

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