A Comparison Study of Weighting Adjustment and Multiple Imputation for Missingness Due to Nonlinkage: A Study of the National Health Interview Survey Linked to Medicare Data Files

• Activity Number: 633
• Type: Topic Contributed
• Date/Time: Thursday, August 7, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Survey Research Methods Section
• Author(s): Guangyu Zhang*+ and Nathaniel Schenker and Jennifer Parker
• Companies: NCHS/CDC and NCHS and NCHS
• Keywords: missing data ; weighting adjustment ; multiple imputation ; linked data

Abstract

Weighting adjustment and multiple imputation are two commonly used methods for missing data issues in surveys. In this talk, we compare results of weighting adjustment and multiple imputation for linked National Health Interview survey and Medicare data files (NHIS-Medicare). We study mammography status based on Medicare claims from 1999 to 2004 for women 65 years and older each year. For NHIS-Medicare data files, mammography information is usually available for participants who consent to have their data linked and who are in the Fee-for-Service Medicare program, but not available for participants who were not linked and less consistently available for participants in the managed care programs, such as Medicare Advantage. In our study, mammography and Medicare Advantage status are missing for NHIS participants not linked to Medicare; and mammography status is missing for some linked participants who have Medicare Advantage coverage. We conduct simulation studies and apply weighting adjustment and multiple imputation methods to the linked NHIS-Medicare files.