Average Reviews:
(More customer reviews)This series is a long and successful collection of volumes on the most important topics in statistics. Professor Krishnaiah from the University of Pittsburgh was one of the first editors. When the famous Professor C. R. Rao moved from India to the US he joined his colleague Krishnaiah at Pittsburgh and helped coedit some of these handbooks. After Krishnaiah's death Professor Rao continued to edit these volumes and brought in some of his colleagues as co-editors.
This is volume 27 and it contains 27 chapters on the topic of medical statistics and epidemiology. This is very important to me as I work in the medical research area.
The editors have assembly the leading experts in statistical methodology and applied biostatistical reserach to produce these 27 chapters.
Ross Prentice (coauthor of 2 edition of a book on survival analysis and the Cox model) wrote an overview chapter on the topics to be covered. He has had a long career at the Fred Hutchinson Cancer Research Center in Seattle Washington. Fred Hutchinson was a famous manager for the Cincinnati Reds in the early 1960s and brought them to the World Series in 1961. He died of cancer and his estate started an endowment to form this research center.
Don Rubin covers causal analysis in Chapter 2. Rubin is an expert on causal inference, Bayesian methods and missing data. He presents the randomized trial approaches of Fisher and Neyman introduces propensity scores. A Bayesian approach is also covered.
Other chapters cover epidemiologic study designs, assessments for biomarkers, linear and nonlinear regression models, logistic regression, regression models for count data, mixed linear and nonlinear models, survival analysis, competing risk models, cluster analysis, factor analysis, structural equation models, crossover trials, group sequential methods, early phase trials (I and II), late phase (III and IV), missing data, Meta-Analysis, multiple comparisons, sample size determination
statistical learning using splines, evidence based medicine, marginal regression models, use of difference equations in modeling and the Bayesian approach to medical inference.
This volume is over 800 pages and each chapter is fairly long and includes large bibliographies.
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