Analysis of covariance in mixed models with unequal subclass numbers

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Abstract
Blue of estimable linear functions and exact tests of hypotheses concerning such functions usually do not exist in the covariance model with random factors having unknown variances. This is true even in the equal subclass numbers case. This paper suggests alternative methods for finding linear unbiased estimators and presents methods for computing sampling variances which are linear functions of the unknown parameter variances. Also, higher level covariates are defined and nonestimability problems resulting from association of such covariates with fixed factors are discussed.