Wiley Series in Probability and Statistics - Applied Probability and Statistics Section – serie

Presenting information on logistic regression models, this work explains difficult concepts through illustrative examples. This is a solutions manual to accompany applied Logistic Regression, 2nd Edition.

With meta-analysis methods playing a crucial role in health research in recent years, this important and clearly-written book provides a much-needed survey of the field.Meta-analysis provides a framework for combining the results of several clinical trials and drawing inferences about the effectiveness of medical treatments. The move towards evidence-based health care and practice is underpinned by the use of meta-analysis. This book:* Provides a thorough criticism and an up-to-date survey of meta-analysis methods* Emphasises the practical approach, and illustrates the methods by numerous examples* Describes the use of Bayesian methods in meta-analysis* Includes discussion of appropriate software for each analysis* Includes numerous references to more advanced treatment of specialist topics* Refers to software code used in the examples available on the authors' Web sitePractising statisticians, statistically-minded clinicians and health research professionals will benefit greatly from the clear presentation and numerous examples. Medical researchers will grasp the basic principles of meta-analysis, and learn how to apply the various methods.

Many problems in statistics and econometrics offer themselves naturally to the use of optimization heuristics. Standard methods applied to highly complex problems often produce approximate results, of unknown quality, based on heavy assumptions. Optimization heuristic methods provide powerful results to many complex problems, combined with relatively simple implementation. The techniques used in optimization heurisitics can be applied to problems encountered in econometrics, statistics and operations research.* Offers a self-contained introduction to optimization heuristics in econometrics and statistics* Features many examples of optimization heuristic methods applied to real problems* Includes detailed coverage of the threshold accepting heuristic methods applied to real problems* Provides suggestions for further readingSplit into three parts, the book opens with a general introduction to optimization in statistics and econometrics, followed by detailed discussion of a relatively new and very powerful optimization heuristic, threshold accepting. The final part consists of many applications of the methods described earlier, encompassing experimental design, model selection, aggregation of time series, and censored quantile regression models.Those researching and working in econometrics, statistics and operations research are given the tools to apply optimization heuristic methods to real problems in their work. Postgraduate students of statistics and econometrics will find the book provides a good introduction to optimization heuristic methods.