Hello Diana.  I don't have a direct answer to your question, but I do have some pointers to material that /may/ be helpful.

• Singer & Willett (/Applied Longitudinal Data Analysis/, Chapter 5) talk about missing data in the multilevel model for change.
• Twisk (/Applied Multilevel Analysis/, 2006, p. 107) says this:
  

"However, when applying multilevel analysis to longitudinal data, there is no need to have a 'complete' dataset, and furthermore, it has been shown that multilevel analysis is very flexible in handling missing data.  It has even been shown that applying multilevel analysis to an incomplete dataset is even better than applying imputation methods (Twisk and de Vente, 2002;Twisk, 2003)."

• Twisk & de Vente (2002):  http://europepmc.org/abstract/MED/11927199
• Twisk (2003):http://books.google.ca/books?hl=en&lr=&id=TCg02e-tI_cC&oi=fnd&pg=PR15&dq=Twisk+2003&ots=2GfodRIiu9&sig=z8BSBQoRaZNavIzj_QOeATBP_nw#v=onepage&q=Twisk%202003&f=false
  

Bruce Weaver, Professor Lakehead University, Canada