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Activity Number: 530 - SPEED: Survey Research Methods
Type: Contributed
Date/Time: Wednesday, August 2, 2017 : 10:30 AM to 11:15 AM
Sponsor: Survey Research Methods Section
Abstract #325316
Title: Multiple Imputation to Evaluate the Impact of an Assay Change in National Surveys
Author(s): Maya Sternberg*
Companies: Centers for Disease Control & Prevention
Keywords: NHANES ; Multuple Imputation ; Assay
Abstract:

National health surveys, such as the National Health and Nutrition Examination Survey (NHANES), 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 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 are 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 NHANES data for 25-hydroxyvitamin D.


Authors who are presenting talks have a * after their name.

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