In a multivariate growth-curve model, the estimator of the parameter matrix is a function of the matrix of the sums of squares and of the cross-products due to error. However, if the assumption of a patterned covariance matrix is valid, then the parameter estimator does not depend on the error matrix. A likelihood ratio test of this patterned covariance matrix is constructed and its distribution is discussed. A numerical example is provided in which the design consists of two treatment groups, with three repeated measures being taken of the three response variables.
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Biochemistry, Genetics and Molecular Biology(all)
- Immunology and Microbiology(all)
- Agricultural and Biological Sciences(all)
- Applied Mathematics