Regression Models for Time Series Analysis
Regression Models for Time Series Analysis
复制标题
DOI：
10.1198/tech.2003.s166
复制
发表时间：
2003-11
期刊：
影响因子：
2.5
通讯作者：
B. Ray
中科院分区：
文献类型：
--
作者：
B. Ray
作者简要回顾了各种方法，并请读者参考Little（1995）等作品了解详情。所提出的分析是基于某些假设，以便可以应用现有的GEE软件。第四章详细讨论了残差诊断的模型选择、检验和图形化方法。总的来说，广义估计方程是使用GEE方法分析连续和离散相关数据的一个很好的介绍性书籍。作者讨论了这四种商业软件的区别，并对用户提出了建议和注意事项。这本书很容易阅读，它假设读者在GLM方面有一些背景。许多例子来自生物医学研究和调查研究，因此它为分析这些领域和其他领域的相关数据提供了很好的指导。
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.