This volume contains pioneering contributions to both the theory and practice of optimal experimental design. Topics include the optimality of designs in linear and nonlinear models, as well as designs for correlated observations and for sequential experimentation. There is an emphasis on applications to medicine, in particular, to the design of clinical trials. Scientists from Europe, the US, Asia, Australia and Africa contributed to this volume of papers from the 11th Workshop on Model Oriented Design and Analysis.
Stochastic models and related statistical procedures play an important part in furthering our understanding of the challenging problems currently arising in areas of application such as the natural sciences, information technology, engineering, image analysis, genetics, energy and finance, to name but a few.
This collection arises from the 12th Workshop on Stochastic Models, Statistics and Their Applications, Wroclaw, Poland.
Combining both theory and applications, this book presents models and methods for the analysis of two- and multidimensional-contingency tables. The author uses a threefold approach, presenting fundamental models and related inference, highlighting their interpretational aspects, and demonstrating their practical usefulness.
Special features and topics include:
* A characteristic motivating example for each topic covered
* Review of classical and recent methodology for analysis of contingency tables
* Emphasis on applications and methods of fitting models using standard statistical tools - such as SPSS, R, and BUGS - and on interpretation of the results
* Elaborated account of association and symmetry models
* Focus on treatment of ordinal variables
* Detailed insight into exact and Bayesian inference
* Presentation of selected advanced topics, including a discussion of the related literature and links to corresponding algorithms
* Up-to-date supplementary material available on the author’s website
An excellent reference for advanced undergraduates, graduate students, and practitioners in statistics as well as biosciences, social sciences, education, and economics, the work may also be used as a textbook for a course on categorical data analysis. Prerequisites include basic background on statistical inference and knowledge of statistical software packages.