Estimating the reliability of an exposure variable in the presence of confounders

Mimi Y. Kim, Bernard S. Pasternack, Raymond J. Carroll, Karen L. Koenig, Paolo G. Toniolo

Research output: Contribution to journalArticle

2 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)1437-1446
Number of pages10
JournalStatistics in Medicine
Volume14
Issue number13
DOIs
StatePublished - Jul 15 1995

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

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