NHANES 1999-2006 DXA Multiple Imputation Data Files - Supplemental Data Files
1999-2006 Dual Energy X-ray Absorptiometry (DXA) Multiple Imputation Data Files
Supplemental Data Files
NOTE: The multiple imputation procedure produced a small number of imputed values with extreme variability for some survey participants. Because of the extreme variability of these imputed values, the data for these participants have been placed in separate files labeled Supplemental Highly Variable Data. Analysts should be aware of the highly variable nature of these imputed DXA data when considering the use of these separate files.
Multiple imputation is a technique that allows analysts to incorporate the extra variability due to imputation into their analyses. Imputed values should not be treated as measured variables without accounting for the extra variability introduced by the imputation process. The extra variability due to imputation CANNOT be incorporated by simply analyzing a SINGLE dataset as if the imputed values were true values. Moreover, analysts SHOULD NOT create a single dataset using the AVERAGE of the five sets of valid and imputed values. The preferred statistical approach is to analyze EACH OF THE FIVE datasets separately using methods and software that are appropriate for survey data and then combining the estimates and standard errors using the combining rules described in Section 4 of the document available via the Technical Documentation for Multiple Imputation link on the 1999-2006 DXA Data page.
Information on the DXA examination, the data files (variable descriptions, file structure, control counts), and codebook are available via the Data File Documentation links on the 1999-2006 DXA Data page. Users interested in analyzing data for several years should note that the variables and file structure are identical for all three release cycles. ANALYSTS ARE STRONGLY ENCOURAGED TO READ BOTH THE TECHNICAL DOCUMENTATION AND THE DATA FILE DOCUMENTATION. Users are also encouraged to check the NHANES What's New website for updates and to subscribe to the NHANES Listserv to receive notices of any corrections/updates.