Adaptive Validation Design

Epidemiology - Tập 31 Số 4 - Trang 509-516 - 2020
Lindsay J. Collin1, Richard F. MacLehose2, Thomas P. Ahern3, Rebecca Nash1, Darios Getahun4, Douglas Roblin5, Michael J. Silverberg6, Michael Goodman1, Timothy L. Lash1
1Department of Epidemiology, Emory University, Atlanta, GA
2Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN
3Department of Surgery, The Robert Larner, M.D. College of Medicine at The University of Vermont, Burlington, VT
4Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA
5Mid-Atlantic Permanente Research Institute, Kaiser Permanente Mid-Atlantic States, Rockville, MD
6Division of Research, Kaiser Permanente Northern California, Oakland, CA

Tóm tắt

An internal validation substudy compares an imperfect measurement of a variable with a gold-standard measurement in a subset of the study population. Validation data permit calculation of a bias-adjusted estimate, which has the same expected value as the association that would have been observed had the gold-standard measurement been available for the entire study population. Existing guidance on optimal sampling for validation substudies assumes complete enrollment and follow-up of the target cohort. No guidance exists for validation substudy design while cohort data are actively being collected. In this article, we use the framework of Bayesian monitoring methods to develop an adaptive approach to validation study design. This method monitors whether sufficient validation data have been collected to meet predefined criteria for estimation of the positive and negative predictive values. We demonstrate the utility of this method using the Study of Transition, Outcomes and Gender—a cohort study of transgender and gender nonconforming people. We demonstrate the method’s ability to determine efficacy (when sufficient validation data have accumulated to obtain estimates of the predictive values that fall above a threshold value) and futility (when sufficient validation data have accumulated to conclude the mismeasured variable is an untenable substitute for the gold-standard measurement). This proposed method can be applied within the context of any parent epidemiologic study design and modified to meet alternative criteria given specific study or validation study objectives. Our method provides a novel approach to effective and efficient estimation of classification parameters as validation data accrue.

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Epidemiology

Tập 31 Số 4

509-516

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