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We propose an adjusted likelihood ratio test of two-factor separability(Kronecker product structure) for unbalanced multivariate repeated measuresdata. Here we address the particular case where the within subject correlationis believed to decrease exponentially in both dimensions (e.g., temporal andspatial dimensions). However, the test can be easily generalized to factorspecific matrices of any structure. A simulation study is conducted to assessthe inference accuracy of the proposed test. Longitudinal medical imaging dataconcerning schizophrenia and caudate morphology illustrates the methodology.

An Adjusted Likelihood Ratio Test for Separability in Unbalanced Multivariate Repeated Measures Data