Analysis of multivariate repeated measures data with a Kronecker product structured covariance matrix

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On matrix variate skew-normal distributions (2005, methodology): “Naik and Rao [7] give a method of analysing this type of data assuming matrix variate normal distribution for X.”
Estimating and Testing a Structured Covariance Matrix for Three-Level Multivariate Data (2011, background): “Several authors (Boik, 1991; Chaganty and Naik, 2002; Dutilleul, 1999; Galecki, 1994; Naik and Rao, 2001; Roy, 2006a,b, 2007; Roy and Khattree, 2003, 2005a,b, 2007; Shults and Morrow, 2002) have observed many advantages of using Kronecker product structure or separable covariance structure over the ”
Models with a Kronecker product covariance structure: Estimation and testing (2008, background): “As noted in the literature, see e.g. Galecki (1994) and Naik and Rao (2001), since (cΨ) ⊗ (c−1Ψ) = Ψ ⊗ Σ, all the parameters of Ψ and Σ are not defined uniquely.”
Covariance pattern mixture models for the analysis of multivariate heterogeneous longitudinal data (2014, unknown): “Each class-distribution is characterized by the separability condition of the total variability into two sources related to the multiple attributes and to the temporal evolution via the Kronecker product, in the same perspective of Naik and Rao (2001).”