Evaluating the exposure and disease relationship with adjustment for different types of exposure misclassification: a regression approach.

Published

Journal Article

Misclassification of exposure can lead to biased results in the epidemiologic research. Available methods accounting for misclassification often require the use of a gold standard or assume non-differential misclassification of exposure. We present a regression approach which can detect and account for different types of misclassification when estimating the exposure and disease relationship. This approach uses two imperfect measures of a dichotomous exposure and does not require a gold standard. Standard statistical packages with a logistic regression module can be used for estimation of parameters through the EM algorithm process. Two examples are used to illustrate the methodology.

Full Text

Duke Authors

Cited Authors

  • Kosinski, AS; Flanders, WD

Published Date

  • October 30, 1999

Published In

Volume / Issue

  • 18 / 20

Start / End Page

  • 2795 - 2808

PubMed ID

  • 10521867

Pubmed Central ID

  • 10521867

International Standard Serial Number (ISSN)

  • 0277-6715

Language

  • eng

Conference Location

  • England