Missing Value in SPSS Mixed Model?

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If one uses repeated in procedure GLM then it appears that all subjects must have values for all combinations of the repeated measures.But using SPSS Mixed Procedure, there is then a non-integer error. How is SPSS actually handling the missing values? Should I use unstructured  covariance matrix?
Thanks for help
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Diana

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关键词：mixed model missing Mixed model value procedure subjects actually repeated appears

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