Example of Differential Misclassification Bias - Nurses Health Study

Melanoma Risk

Lead Author(s): Jeff Martin, MD

Differential Misclassification of Exposure Variables

A good verified example of differential misclassification bias can be seen in a Weinstock's nested case control study within the Nurses Health Study that looked at the association between one's self-reported tanning ability and melanoma.


Here, the cases were women with new melanoma diagnoses and controls were women without melanoma, sampled by incidence density sampling.


The 2x2 table below shows what the results of the questionnaire.

The reference group is women who report medium to dark tanning ability. Is there any reason to be suspicious about this?

Well, it is conceivable that when questioned after the diagnosis of melanoma, some participants may have exaggerated their lack of tanning ability especially if they were concerned that sun exposure was a reason they got melanoma.

Comparison with Cohort Study Data

Because this was a cohort study, the investigators had the ability to look at responses to the tanning ability question was answered at the baseline of the study - long before the melanoma diagnosis. In the 2x2 table below we see the results of the questionnaire before diagnosis.


When they looked at the question answered at the Nurses Health Study baseline, they found no evidence of an association between tanning ability and melanoma.

Schematic of Differential Misclassification

What apparently occurred is shown schematically below.


If we consider the responses given at baseline to be the gold standard (and these responses were, of course, given prior to any occurrence of melanoma and hence they are most believable), This is an example of DIFFERENTIAL misclassification of exposure, and the bias is away from the null.


Weinstock, M. A., Colditz, G. A., Willett, W. C., Stampfer, M. J., Rosner, B., & Speizer, F. E. (1991). Recall (report) bias and reliability in the retrospective assessment of melanoma risk. Am J Epidemiol, 133 (3), 240-245.