Semantic and cognitive tools to aid statistical science: replace confidence and significance by compatibility and surprise.

ABSTRACT:

Background

Researchers often misinterpret and misrepresent statistical outputs. This abuse has led to a large literature on modification or replacement of testing thresholds and P-values with confidence intervals, Bayes factors, and other devices. Because the core problems appear cognitive rather than statistical, we review some simple methods to aid researchers in interpreting statistical outputs. These methods emphasize logical and information concepts over probability, and thus may be more robust to common misinterpretations than are traditional descriptions.

Methods

We use the Shannon transform of the P-value p, also known as the binary surprisal or S-value s = -log₂(p), to provide a measure of the information supplied by the testing procedure, and to help cal

SUBMITTER: Rafi Z 

PROVIDER: S-EPMC7528258 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature