Two graphical techniques useful in detecting correlation structure in repeated measures data

Analysis of repeated measures data using a mixed model includes specifying a form for the covariance matrix of the within-subject observations. This reduction in the number of estimated parameters from the unspecified structure may improve the efficiency of inferences made. An implementation of this technique has been incorporated in the MIXED procedure of the SAS(R) statistical package, and includes a wide range of options for the structure of the covariance matrix. It is demonstrated that, draftman's display plots and/or plots in a coordinate system with parallel axes can aid in visualizing the dispersion structure.