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Identifiability of the random effects’ covariance matrix of the linear mixed model

Author

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  • Matteo Amestoy
  • Mark A. van de Wiel
  • Wessel N. van Wieringen

Abstract

Novel necessary and sufficient conditions for the identifiability of the linear mixed model are derived. These conditions either relax or generalize previously reported conditions. The novel conditions are translated to criteria that can be checked for most commonly employed parametrizations of the random effect’s covariance matrix of linear mixed model.

Suggested Citation

  • Matteo Amestoy & Mark A. van de Wiel & Wessel N. van Wieringen, 2024. "Identifiability of the random effects’ covariance matrix of the linear mixed model," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 53(21), pages 7711-7722, November.
    • Handle: RePEc:taf:lstaxx:v:53:y:2024:i:21:p:7711-7722
    DOI: 10.1080/03610926.2023.2272003
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