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Activity Number: 583
Type: Contributed
Date/Time: Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
Sponsor: Section on Survey Research Methods
Abstract - #305731
Title: Imputation Models to Estimate Mean Fatty Acid Percentages in NHANES
Author(s): Maya Sternberg*+ and Rosemary Schleicher
Companies: CDC and CDC
Address: 1600 Clifton Road, NE, Atlanta, GA, 30333, United States
Keywords: NHANES ; imputation ; missing data

We undertook an investigation to assess the impact of missing data when computing percentages of plasma fatty acids (FA) by comparing a variety of imputation models. Plasma FA are short-term biomarkers accounting for several weeks of dietary intake. Twenty-four FA are measured as part of National Health and Nutrition Examination Survey (NHANES)- a complex, multistage, area probability sample of the US non-institutionalized civilian population. While measured in absolute concentrations, individual FA are most often reported as percentages of total FA. Due to the logistics and cost of obtaining complete profiles of the 24 FA for all NHANES respondents and other issues of multi-analyte quality control, a certain amount of missing data is expected. We assessed imputation models using Markov chain Monte Carlo under multivariate Normality with and without random effects. In general the estimates based on multiple imputation had better statistical properties than simpler alternatives such as complete case analysis. We also found accounting for the sampling design did not seem to be as important as the amount of missing data and which FA were missing.

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