Evaluating the exposure and disease relationship with adjustment for different types of exposure misclassification: a regression approach
✍ Scribed by Andrzej S. Kosinski; W. Dana Flanders
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 107 KB
- Volume
- 18
- Category
- Article
- ISSN
- 0277-6715
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✦ Synopsis
Misclassiÿcation of exposure can lead to biased results in the epidemiologic research. Available methods accounting for misclassiÿcation often require the use of a gold standard or assume non-di erential misclassiÿcation of exposure. We present a regression approach which can detect and account for di erent types of misclassiÿcation 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.