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Estimating the reliability of an exposure variable in the presence of confounders
Author(s) -
Kim Mimi Y.,
Pasternack Bernard S.,
Carroll Raymond J.,
Koenig Karen L.,
Toniolo Paolo G.
Publication year - 1995
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780141304
Subject(s) - confounding , statistics , reliability (semiconductor) , variable (mathematics) , econometrics , mathematics , computer science , mathematical analysis , power (physics) , physics , quantum mechanics
Abstract In this paper we discuss estimation of the reliability of an exposure variable in the presence of confounders measured without error. We give an explicit formula that shows how the exposure becomes less reliable as the degree of correlation between the exposure and confounders increases. We also discuss biases in the corresponding logistic regression estimates and methods for correction. Data from a matched case‐control study of hormone levels and risk of breast cancer are used to illustrate the methods.