🔗 Berkson's Paradox

🔗 Statistics

Berkson's paradox also known as Berkson's bias or Berkson's fallacy is a result in conditional probability and statistics which is often found to be counterintuitive, and hence a veridical paradox. It is a complicating factor arising in statistical tests of proportions. Specifically, it arises when there is an ascertainment bias inherent in a study design. The effect is related to the explaining away phenomenon in Bayesian networks, and conditioning on a collider in graphical models.

It is often described in the fields of medical statistics or biostatistics, as in the original description of the problem by Joseph Berkson.