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A family of multivariate linear growth curve models with random effects is considered. The purpose of this article is to describe a computational method required for the estimation of individual regression coefficients when the covariance components are known or unknown. In the second case, the covariance matrix of the data will be estimated by a generalized version of the Henderson method III using the orthogonal projections onto linear subspaces corresponding to the model, and a two-stage estimator of individual regression coefficients is obtained. The estimation of fixed and random effects is presented in a Bayesian approach.
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