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Modelling issues in multi-unit longitudinal models with random coefficients and patterned correlation structure are illustrated in the context of three data sets. The first data set deals with short time series data on annual death rates and alcohol consumption of twenty-five European countries. The second data set deals with glaceologic time series data on snow temperature at 14 different locations within a small glacier in the Austrian Alps. The third data set consists of annual economic time series on factor productivity, and domestic and foreign research/development (R&D) capital stocks. A practical model building approach–consisting of model specification, estimation, and diagnostic checking–is outlined in the context of these three data sets.

Case Studies in Multi-unit LongitudinalModels with Random Coefficients and Patterned Correlation Structure