Conditional Linear Mixed Models

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Multilevel Modeling with Correlated Effects (2007, background): “Verbeke, Spiessens, and Lesaffre (2001) described observational clinical studies where t =1 corresponds to baseline measurements and the explanatory variables are interpreted in terms of changes from the baseline.”
Bayesian Multilevel Analysis and MCMC (2008, background): “In particular, the latest versions of MLwiN (the successor to ML3; [60]) and HLM [66] have worldwide user bases in the social and biomedical sciences numbering in the thousands, and likelihood-based fitting of at least some multilevel models is also now obtainable in more general-purpose statistical”
Omitted Variables in Multilevel Models (2006, methodology): “Another possibility, proposed by Verbeke, Spiessens, and Lesaffre (2001) , is to assume that omitted effects are part of the subject-specific error term but not part of subject-specific slopes.”
Separating between‐ and within‐cluster covariate effects by using conditional and partitioning methods (2006, background): “In related work, Verbeke et al. (2001) showed that misspecification of the relationship between the cross-sectional and longitudinal components of linear mixed effects models can yield inconsistent parameter estimates and that conditional likelihood methods provide consistent estimation.”