multilevel

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by …

We present and compare multiple imputation methods for multilevel continuous and binary data where variables are systematically and sporadically missing. The methods are compared from a theoretical point of view and through an extensive simulation …

This chapter discusses critical issues associated with imputation of multilevel data. Section 10.2 introduces the notation used and outlines how two formulations of the same model are related. Section 10.3 dissects the multilevel missing data problem …