Model averaging and weight choice in linear mixed-effects models

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Model averaging based on leave-subject-out cross-validation (2016, background): “A related work dealing with longitudinal data was done by Zhang et al. (2014).”
Weighted‐Average Least Squares (WALS): A Survey (2016, methodology): “…(Claeskens et al., 2006); models for survival analysis (Hjort and Claeskens, 2006); generalized additive partial linear models (Zhang and Liang, 2011); Tobit models (Zhang et al., 2012); multinomial and ordered logit models (Wan et al., 2014); and linear mixed-effects models (Zhang et al., 2014).”
Optimal Model Averaging Estimation for Generalized Linear Models and Generalized Linear Mixed-Effects Models (2016, methodology): “Condition C.3 requires that ξn grows at a rate no slower than n1/2, is the same as the third part of Condition (A7) of Zhang, Zou, and Liang (2014) and is also implied by Conditions (7) and (8) of Ando and Li (2014).”