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Studies with low response proportions may be less biased than studies with high response proportions
Andreas Stang1, Karl-Heinz Jöckel
1Epidemiology Unit, Institute for Medical Informatics, Biometry and Epidemiology, University Hospital, University of Duisburg-Essen, Essen, Germany. andreas.stang@uni-essen.de
Abstract:
The association between the response proportion in epidemiologic studies and nonresponse bias is complicated, because exposure prevalences and misclassification errors may vary by recruitment wave. In this paper, the authors illustrate the effect of varying degrees of wave-specific nondifferential exposure measurement error in a dichotomous exposure on the relative risk in a hypothetical cohort study of 5,000 participants, by recruitment wave. The field phase of the hypothetical cohort study consisted of five consecutive recruitment waves. The authors assigned response proportions to each wave (wave 1: 30%; wave 2: 10%; wave 3: 10%; wave 4: 30%; wave 5: 20%) and studied three different wave-specific patterns of true exposure prevalence: 1) the true exposure prevalence remains the same in all waves; 2) the true exposure prevalence increases by wave; and 3) the true exposure prevalence decreases by wave. The authors assumed three corresponding patterns of nondifferential misclassification error in exposure status across waves. If the nondifferential exposure misclassification increases by wave, the cumulative relative risk estimate is increasingly biased towards the null. This bias is intensified if the true exposure prevalence increases by wave. Studies with low response proportions may be less biased than studies with high response proportions if the nondifferential misclassification error in a dichotomous exposure increases by recruitment wave.
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