Blus Residuals in Multivariate Linear Models

  • Vernon M. Chinchilli
Part of the Theory and Decision Library book series (TDLB, volume 8)


The examination of residuals is always an important aspect of fitting data to statistical models in terms of identifying influential observations and detecting violations of assumptions. The latter use is difficult to perform for the ordinary residuals in the univariate linear model because these residuals are not independent. This led researchers to consider alternative sets of residuals, such as the best linear, unbiased, scalar-type variance (BLUS) residuals. In this article the definition of BLUS residuals is extended to multivariate models. The extension is relatively straightforward for the multivariate analysis of variance (MANOVA) model, but not for the generalized multivariate analysis of variance (GMANOVA) model and the mixed MANOVA-GMANOVA model. For each of the GMANOVA and mixed MANOVA-GMANOVA models two sets of BLUS residuals arise naturally, namely, a “between” set and a “within” set.

Key words and phrases

MANOVA GMANOVA residual analysis 


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Copyright information

© D. Reidel Publishing Company, Dordrecht, Holland 1987

Authors and Affiliations

  • Vernon M. Chinchilli
    • 1
  1. 1.Department of Biostatistics, Medical College of VirginiaVirginia Commonwealth UniversityRichmondUSA

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