Abstract
Background
Case–control study is still one of the most commonly used study designs in epidemiological research. Misclassification of case–control status remains a significant issue because it will bias the results of a case–control study. There exist two types of misclassification, differential versus nondifferential. It is commonly accepted that nondifferential misclassification will bias the results of the study towards the null hypothesis. Conversely, no reports have assessed the impact and direction of differential misclassification on odds ratio (OR) estimate. The goal of the present study is to demonstrate by statistical derivation that patterns exist on the bias induced by differential misclassification.
Methods
Based on a 2 × 2 case–control study design, we derive the odds ratio without misclassification, and those with misclassification according to: (1) controls are misclassified as cases by exposure status; (2) cases are misclassified as controls by exposure status; and (3) both controls and cases are misclassified by exposure status simultaneously. Furthermore, mathematical derivations are shown for each of the ratios of the two odds ratios with and without misclassification. These methods are carried out by simulation analyses.
Results
Simulation analyses show that quite a number of biased odds ratios tend to move away from the null hypothesis and result in approaching zero or infinity with increasing proportion of misclassification among cases, controls, or both. These patterns are associated with the exposure status and the values of unbiased odds ratio (<1, 1, or >1).
Conclusions
Our findings suggest that, unlike nondifferential misclassification, differential misclassification of case–control status in a case–control study may not weaken the exposure–outcome association towarding the null hypothesis. Care needs to be taken for interpreting the results of a case–control study when there exists differential misclassification bias, a practical issue in epidemiological research.
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Appendix
Appendix
The patterns (towards null or not) of biased odds ratios (RR i , i = 1,...,15) can be investigated by dividing equations (1)–(15) by ORu = ad/bc. The results are shown as follows:
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Chyou, PH. Patterns of bias due to differential misclassification by case–control status in a case–control study. Eur J Epidemiol 22, 7–17 (2007). https://doi.org/10.1007/s10654-006-9078-x
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DOI: https://doi.org/10.1007/s10654-006-9078-x