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Title: Addressing the algebraic structure of a linear mixed model with balanced design towards model extension
Authors: Santos, Carla
Dias, Cristina
Brites, Nuno M.
Nunes, Célia
Mexia, João Tiago
Keywords: Algebraic structure
Balanced mixed model
Best linear unbiased estimators
Issue Date: 2024
Publisher: WILEY
Citation: Santos, C., Dias, C., Brites, N. M., Nunes, C., & Mexia, J. M. (2024). Addressing the algebraic structure of a linear mixed model with balanced design towards model extension. Mathematical Methods in the Applied Sciences. Advance online publication.
Abstract: Linear mixed models provide a general and versatile approach for analyzing data collected in experiments, suitable for modeling repeated, longitudinal, or clustered observations. Important results for estimation can be obtained when subclasses of these mixed models are considered, based on some characteristics of their algebraic structure. The class of the models with commutative orthogonal block structure, for which least squares estimators are the best linear unbiased estimators, is of great interest. In an approach based on the algebraic structure of the models, and availing ourselves of U matrices, we study the possibility of extending a balanced mixed model, which could lead to a model with commutative orthogonal block structure.
Peer reviewed: yes
Publisher version:
Appears in Collections:D-MCF - Artigos em revistas indexadas à WoS/Scopus

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