Joseph Berkson (1899 – 1982) was initially trained as a physicist. Later in his career he became primarily concerned with studying statistics.[1] In 1950, while working at the Division of Biometry and Medical Statistics, Mayo Clinic, Rochester, Minnesota, Berkson wrote a key paper entitled Are there two regressions?.[2] In this paper Berkson proposed an error model for regression analysis that contradicted the classical error model until that point assumed to generally apply and this has since been termed the Berkson error model. Whereas the classical error model is statistically independent of the true variable, Berkson's model is statistically independent of the observed variable.[3] Carroll et al. (1995)[4] refer to the two types of error models as follows:
Berkson is also widely recognised as the key proponent in the use of the logistic in preference to the normal distribution in probabilistic techniques.[1] Berkson is also credited with the introduction of the logit model in 1944[5], and with coining this term. The term was borrowed by analogy from the very similar probit model developed by Chester Ittner Bliss in 1934.
Berkson was a prominent opponent of the idea that cigarette smoking causes cancer. In the 1957 Liggett & Myers annual report, he was quoted as saying "the evidence, taken as a whole, does not establish, on any reasonable scientific basis, that cigarette smoking causes lung cancer."[6] Following the issuance of the famous report Smoking and Health: Report of the Advisory Committee to the Surgeon General of the United States, he was quoted in Life Magazine as saying it was "very doubtful that smoking causes cancer of the lung."[7]
Berkson:
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