Statistical Analysis With Missing Data

authors brie y review various methods and refer readers to works such as Little (1995) for details. The analyses presented are based on certain assumptions, such that the available GEE software can be applied. Chapter 4 gives a thorough discussion on model selection and testing and graphical methods for residual diagnostics. Overall, Generalized Estimating Equations is a good introductory book for analyzing continuous and discrete correlated data using GEE methods. The authors discuss the differences among the four commercial software programs and provide suggestions and cautions for users. This book is easy to read, and it assumes that the reader has some background in GLM. Many examples are drawn from biomedical studies and survey studies, and so it provides good guidance for analyzing correlated data in these and other areas.