Multiple imputation to account for linkage ineligibility in the NHANES-CMS Medicaid linked data: General use versus subject specific imputation models1
Affiliations: Division of Research and Methodology, National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, MD, USA
Correspondence:
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Corresponding author: Jennifer Rammon, Centers for Disease Control and Prevention, National Center for Health Statistics, Division of Research and Methodology, HYAT Bldg IV Cube 4108 MS 08, Hyattsville, MD 20782-2064, USA. Tel.: +1 301 458 4865; E-mail: lmi3@cdc.gov.
Note: [1] Disclaimer: The findings and conclusions in this paper are those of the authors and do not necessarily represent the views of the National Center for Health Statistics, Centers for Disease Control and Prevention.
Abstract: Data from the National Health and Nutrition Examination Survey (NHANES) have been linked to the Center for Medicare and Medicaid Services’ Medicaid Enrollment and Claims Files. As not all survey participants provide sufficient information to be eligible for record linkage, linked data often includes fewer records than the original survey data. This project presents an application of multiple imputation (MI) for handling missing Medicaid/CHIP status due to linkage refusals in linked NHANES-Medicaid data using the linked 1999–2004 NHANES data. By examining multiple outcomes and subgroups among children, the analyses compare the results from a multi-purpose dataset produced from a single MI model to that of individualized MI models. Outcomes examined here include obesity, untreated dental caries, attention deficit hyperactivity disorder (ADHD), and exposure to second hand smoke.
Keywords: Children, data linkage, NHANES, Medicaid, multiple imputation
