Abstract:
:This paper considers the effect of non-differential outcome misclassification on the population attributable fraction and the population prevented fraction. I examine the bias in the attributable and the prevented fraction derived from a risk ratio estimate as a function of the sensitivity and specificity of the outcome classification, the true risk ratio, the prevalence of the exposure, and the baseline disease frequency. With outcome misclassified, disease frequency is an important determinant of the magnitude of the bias; the rarer the disease, the more severe is the bias. For both the attributable and the prevented fraction, the specificity of the outcome classification has a greater influence on the magnitude of the bias than the sensitivity; this is in contrast to the dominant effect of sensitivity in situations of exposure misclassification. Also, unlike the findings in the exposure misclassification, the bias due to outcome misclassification does not increase monotonically with increased prevalence of exposure. For the attributable and prevented fraction derived from an odds ratio estimate, the specificity of the outcome classification does not have a greater influence on bias than the sensitivity, and a perfect specificity alone does not lead to unbiased effect estimates if the sensitivity of the outcome classification is imperfect.
journal_name
Stat Medjournal_title
Statistics in medicineauthors
Hsieh CCdoi
10.1002/sim.4780100308subject
Has Abstractpub_date
1991-03-01 00:00:00pages
361-73issue
3eissn
0277-6715issn
1097-0258journal_volume
10pub_type
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