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I have endeavored to provide a comprehensive introduction to a wide - riety of statistical methods for the analysis of repeated measurements. I envision this book primarily as a textbook, because the notes on which it is based have been used in a semester-length graduate course I have taught since1991.Thiscourseisprimarilytakenbygraduatestudentsinbiostat- tics and statistics, although students and faculty from other departments have audited the course. I also anticipate that the book will be a useful r- erence for practicing statisticians. This assessment is based on the positive responses I have received to numerous short courses I have taught on this topic to academic and industry groups. Althoughmyintentistoprovideareasonablycomprehensiveoverviewof methodsfortheanalysisofrepeatedmeasurements,Idonotviewthisbook as a de?nitive "e;state of the art"e; compendium of research in this area. Some general approaches are extremely active areas of current research, and it is not feasible, given the goals of this book, to include a comprehensive summary and list of references. Instead, my focus is primarily on methods that are implemented in standard statistical software packages. As a result, thelevelofdetailonsometopicsislessthaninotherbooks,andsomemore recent methods of analysis are not included. One particular example is the topic of nonlinear mixed models for the analysis of repeated measurements (Davidian and Giltinan, 1995; Vonesh and Chinchilli, 1996). With respect to some of the more recent methods of analysis, I do attempt to mention some of the areas of current research.
A comprehensive introduction to a wide variety of statistical methods for the analysis of repeated measurements. It is designed to be both a useful reference for practitioners and a textbook for a graduate-level course focused on methods for the analysis of repeated measurements.
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