Bayesian local influence in growth curve model with unstructured covariance

From the Bayesian point of view, a local influence approach is developed to diagnose the adequacy of the growth curve model with an unstructured covariance. Based on the Kullback-Leibler divergence, the Bayesian Hessian matrices of the parameters in the model are studied under an abstract perturbation scheme and the eigenvector associated with the largest eigenvalue of the Hessian matrix is used to identify influential observations. For illustration, the covariance-weighted perturbation, a commonly encountered perturbation, is considered particularly and used to analyze a practical data set. Comparisons with the likelihood-based local influence are also made.