✳flâneur — a map of the web's best reading

Berkson's paradox - Wikipedia

en.m.wikipedia.org · 2,057 words · saved by 1 readers

Berkson's paradox, also known as Berkson's bias, collider 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. The most common example of Berkson's paradox is a false observation of a negative correlation between two desirable traits, i.e., that members of a population which have some desirable trait tend to lack a second. Berkson's paradox occurs when this observation appears true when in reality the two properties are unrelated—or even positively correlated

Berkson's paradox - Wikipedia Jump to content From Wikipedia, the free encyclopedia Tendency to misinterpret statistical experiments involving conditional probabilities This article includes a list of references , related reading , or external links , but its sources remain unclear because it lacks inline citations . Please help improve this article by introducing more precise citations. ( March 2023 ) ( Learn how and when to remove this message ) An example of Berkson's paradox: Top: a graph where talent and attractiveness are uncorrelated in the population. Bottom: The same graph truncated t

Explore this link on the map →