ABSTRACT
Hierarchical organization of schooling in all nations ensures that international large-scale assessment data are multilevel where students are nested within schools and schools are nested within nations. Longitudinal followup of these students adds an additional level. Hierarchical or multilevel models are appropriate to analyze such data (Raudenbush and Bryk 2002; Goldstein 2003). A ubiquitous problem, however, is that explanatory as well as outcome variables may be subject to missingness at any of the levels, posing the data analyst with a challenge.
