Multiple imputation to evaluate the impact of an assay change in national surveys. (16th April 2017)

• Record Type: Journal Article
• Authors: Sternberg, Maya
• Is Part Of: Statistics in medicine. Volume 36:Number 17(2017)
• Page Start: 2697
• Page End: 2719
• Publication Date: 2017-04-16
• Subjects: multiple imputation -- NHANES -- assay change -- vitamin D; Medical statistics -- Periodicals; Statistique médicale -- Périodiques; Statistiques médicales -- Périodiques; 610.727
• DOI: 10.1002/sim.7302
• Languages: English
• ISSNs: 0277-6715

Abstract

Abstract : National health surveys, such as the National Health and Nutrition Examination Survey, are used to monitor trends of nutritional biomarkers. These surveys try to maintain the same biomarker assay over time, but there are a variety of reasons why the assay may change. In these cases, it is important to evaluate the potential impact of a change so that any observed fluctuations in concentrations over time are not confounded by changes in the assay. To this end, a subset of stored specimens previously analyzed with the old assay is retested using the new assay. These paired data are used to estimate an adjustment equation, which is then used to 'adjust' all the old assay results and convert them into 'equivalent' units of the new assay. In this paper, we present a new way of approaching this problem using modern statistical methods designed for missing data. Using simulations, we compare the proposed multiple imputation approach with the adjustment equation approach currently in use. We also compare these approaches using real National Health and Nutrition Examination Survey data for 25‐hydroxyvitamin D. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.