Analyzing the Multiply Imputed Accelerometer Data in the 2003-2004 National Health and Nutrition Examination Survey

• Activity Number: 318 - Analyzing Government Data with Missing Item Values: A WSS Invited Session
• Type: Invited
• Date/Time: Tuesday, August 1, 2017 : 10:30 AM to 12:20 PM
• Sponsor: Host Chapter
• Author(s): Benmei Liu* and Mandi Yu and Barry I. Graubard and Richard Troiano and Nathaniel Schenker
• Companies: National Cancer Institute and National Cancer Institute and National Cancer Institute and National Cancer Institute and Retired
• Keywords: Accelerometer data ; missing ; primary sampling units ; multiple imputation ; regression analysis

Abstract

The Physical Activity Monitor component was introduced into the 2003-2004 National Health and Nutrition Examination Survey (NHANES) to collect objective information on physical activity including both movement intensity counts and ambulatory steps. Due to an error in the accelerometer device initialization process, the steps data were missing for all participants in several primary sampling units, typically single counties or groups of contiguous counties, who had intensity count data from their accelerometers. To avoid potential bias and loss in efficiency in estimation and inference involving the steps data, we adopted a multiple imputation approach based on Additive Regression, Bootstrapping and Predictive mean matching methods to accurately impute the missing values for steps collected in the 2003-2004 NHANES. This paper describes several real data analyses using the multiply imputed data and compares them with the before imputation results.