The Berkson error model is a description of

random error Observational error (or measurement error) is the difference between a measured value of a quantity and its true value.Dodge, Y. (2003) ''The Oxford Dictionary of Statistical Terms'', OUP. In statistics, an error is not necessarily a "mistake" ...

(or misclassification) in measurement. Unlike

classical error In statistics and optimization, errors and residuals are two closely related and easily confused measures of the deviation of an observed value of an element of a statistical sample from its "true value" (not necessarily observable). The error ...

, Berkson error causes little or no bias in the measurement. It was proposed by Joseph Berkson in an article entitled “Are there two regressions?,” published in 1950. An example of Berkson error arises in

exposure assessment Exposure assessment is a branch of environmental science and occupational hygiene that focuses on the processes that take place at the interface between the environment containing the contaminant of interest and the organism being considered. ...

in epidemiological studies. Berkson error may predominate over

in cases where exposure data are highly aggregated. While this kind of error reduces the

power Power most often refers to: * Power (physics), meaning "rate of doing work" ** Engine power, the power put out by an engine ** Electric power * Power (social and political), the ability to influence people or events ** Abusive power Power may a ...

of a study, risk estimates themselves are not themselves attenuated (as would be the case where

predominates).

References

Further reading