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Legend:  = Applied Session,
 = Theme Session,
 = Presenter
FRY = Fairmont Royal York, ICH = InterContinental Hotel, TCC = Metro Toronto Convention Center
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CE_11C
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Sun, 8/8/04, 8:15 AM - 4:15 PM
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FRY-Manitoba
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Longitudinal and Incomplete Data (1 Day Course) - Continuing Education - Course
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ASA, Section on Statistics in Epidemiology
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Instructor(s): Geert Verbeke, Katholieke Universiteit Leuven, Geert Molenberghs, Limburgs Universitair Centrum
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A general introduction to longitudinal data and the linear mixed model for continuous responses will be presented. The topic will be approached from the modeler's and practitioner's points of view, with emphasis on model formulation, inference and parameter interpretation. Illustrations will be given based on the SAS procedure MIXED.
When the response of interest is categorical, the linear mixed model concepts can be extended towards generalized linear mixed models. An alternative approach is the use of generalized estimating equations (GEE). A lot of emphasis will be put on the fact that the regression parameters in both types of models have different interpretations, and illustrations will be based on the SAS procedures GENMOD and NLMIXED.
Finally, when analyzing longitudinal data, one is often confronted with incomplete observations, i.e., scheduled measurements have not been made, due to a variety of (known or unknown) reasons. It will be shown that, if no appropriate measures are taken, missing data can cause seriously biased results, and interpretational difficulties.
Throughout the course, it will be assumed that the participants are familiar with basic statistical modeling, including linear and generalized linear models.
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