ARHIV DRUŽBOSLOVNIH PODATKOV

Based on Verbeke and Molenberghs (2000), we first present linear mixed models for continuous hierarchical data. The focus lies on the modeler's perspective and on applications. Emphasis will be on model formulation, parameter estimation, and hypothesis testing, as well as on the distinction between the random-effects (hierarchical) model and the implied marginal model. Apart from classical model building strategies, many of which have been implemented in standard statistical software, a number of flexible extensions and additional tools for model diagnosis will be indicated. A number of illustrations and worked examples will be given based on the SAS procedure MIXED.