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Separability in ordinary regression is achieved by partitioning the set of explanatory variables into mutually orthogonal subsets. The coefficient vector of each subset is separate: its estimate depends only on the response and on the explanatory variable scores of the subset. The feasibility of formulating multilevel models with subsets of separate(More)
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