Patterns of residual covariance structure
Abstract
Chapter 5 concentrates on a linear regression approach on longitudinal data in which the structure of the residual variance–covariance matrix is specified while the covariance matrix for the random effects is left unspecified. A number of residual variance–covariance pattern models are exhibited, including those applied either in situations where repeated measurements are equally spaced or in the analysis of longitudinal data with irregular time intervals. Next, strategies to select an appropriate residual variance–covariance structure are summarized. Scaling techniques for the time factor are then displayed. An overview is provided for the definition of a classification factor, with ...
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