Identifying the sources and measuring the impact of haphazard variations are important in any number of research applications, from clinical trials and genetics to industrial design and psychometric testing. Only in very simple situations can such variations be represented effectively by independent, identically distributed random variables or by random sampling from a hypothetical infinite population.
Components of Variance illuminates the complexities of the subject, setting forth its principles with focus on both the development of models for detailed analyses and the statistical techniques themselves. The authors first consider balanced and unbalanced situations, then move to the treatment of non-normal data, beginning with the Poisson and binomial models and followed by extensions to survival data and more general situations. In the final chapter, they discuss ways of extending and assessing various models, including the study of exceedances, the use of nonlinear representations, the study of transformations of the response variable, and the detailed examination of the distributional form of the underlying random variables.
Careful signposting and numerous examples from genetic data analysis, clinical trial design, longitudinal data analysis, industrial design, and meta-analysis make this book accessible - and valuable - not only to statisticians but to all applied research scientists who use statistical methods.
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Cox, D.R.; Solomon, P.J.
The book succeeds in providing a good starting point for a statistician interested in an introduction to many of the issues associated with variance component estimation. ... [V]ery approachable to a statistician with little background in the analysis of mixed models.
- Journal of the Americal Statistical Association, Sept. 2004, Vol. 99, No. 467
Components of Variance is easy to read and to find examples. Its main features are the excellent discussions of the various models and the wealth of examples.
-Technometrics, 2003
This is a superb book on a topic of central importance in a wide variety of areas of research. A particular strength is attention given to first principles as a prelude to the treatment of many of the technical topics. .... What distinguishes this book from other material is the depth of the discussion combined with the use of only essential technical details.
-Vern Farewell, MRC Biostatistics Unit, Institute of Public Health, Cambridge, UK
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