Distortions that arise when the people, cases or data examined are not representative of the whole, such as survivorship bias and selection bias. A phenomenon belongs here when its cited article describes a distortion from who or what was selected. Every member sits in the Psychology Atlas as its own page with a definition, cited sources and links to related effects, so the group works as a reading path through Selection and Sampling Biases rather than as a claim that the members share one cause. Where scholars disagree about how an effect should be classified, the member page says so.
All Selection and Sampling Biases
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Wikipedia: Survivorship bias
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Survivorship bias or survivor bias is a statistical error which results from concentrating on entities that passed a selection process over those that did not.
Wikipedia: Selection bias
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Selection bias is the bias introduced by the selection of individuals, groups, or data for analysis in such a way that the association between exposure and outcome among those selected for analysis differs from the association among those eligible.
Wikipedia: Participation bias
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Participation bias or non-response bias is a phenomenon in which the results of studies, polls, etc. become non-representative because the participants disproportionately possess certain traits which affect the outcome.
Wikipedia: Berkson's paradox
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Berkson's paradox, also known as Berkson's bias, collider bias, endogenous selection 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.
Regression toward the mean - Wikipedia
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In statistics, regression toward the mean (also called regression to the mean, reversion to the mean, and reversion to mediocrity) is the phenomenon where if one sample of a random variable is extreme, the next sampling of the same random variable is likely to be closer to its mean.
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