The effect of non-differential outcome misclassification on estimates of the attributable and prevented fraction.

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 Med

journal_title

Statistics in medicine

authors

Hsieh CC

doi

10.1002/sim.4780100308

subject

Has Abstract

pub_date

1991-03-01 00:00:00

pages

361-73

issue

3

eissn

0277-6715

issn

1097-0258

journal_volume

10

pub_type

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