L models and multiple regressions designs

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9 Citations (Scopus)


Given an orthogonal model an L model is obtained, and the only restriction is the linear independency of the column vectors of matrix L. Special cases of the L models correspond to blockwise diagonal matrices L = D(L1,..., Lc). In multiple regression designs this matrix will be of the form L = D(X̌1,..., X̌c)with X̌j, j = 1,...,c the model matrices of the individual regressions, while the original model will have fixed effects. In this way, we overcome the usual restriction of requiring all regressions to have the same model matrix.

Original languageEnglish
Pages (from-to)869-885
Number of pages17
JournalStatistical Papers
Issue number4
Publication statusPublished - 5 Aug 2009
EventInternational Conference on Trends and Perspectives in Linear Statistical Inference, LinStat'2008 - Bedlewo, Portugal
Duration: 21 Apr 200825 Apr 2008


  • Commutative Jordan algebras
  • Cross-nested models
  • L models
  • Multiple regression models
  • Orthogonal models


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