A pedagogical tool is presented for applied researchers dealing with incomplete multilevel, longitudinal data. It explains why such data pose special challenges regarding missingness. Syntax created to perform a multiply-imputed growth modeling procedure in Stata Version 11 (StataCorp, 2009) is also described.
Lloyd, Jennifer E. V.; Obradović, Jelena; Carpiano, Richard M.; and Motti-Stefanidi, Frosso
"JMASM 32: Multiple Imputation of Missing Multilevel, Longitudinal Data: A Case When Practical Considerations Trump Best Practices?,"
Journal of Modern Applied Statistical Methods: Vol. 12
, Article 29.
Available at: http://digitalcommons.wayne.edu/jmasm/vol12/iss1/29