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Analysis of Mixed Data Now Available from CRC Press

A comprehensive source on mixed data analysis, Analysis of Mixed Data: Methods & Applications summarizes the fundamental developments in the field.

PRLog - Jan. 30, 2013 - BOCA RATON, Fla. -- A comprehensive source on mixed data analysis, Analysis of Mixed Data: Methods & Applications summarizes the fundamental developments in the field. Case studies are used extensively throughout the book to illustrate interesting applications from economics, medicine and health, marketing, and genetics.

Carefully edited for smooth readability and seamless transitions between chapters
All chapters follow a common structure, with an introduction and a concluding summary, and include illustrative examples from real-life case studies in developmental toxicology, economics, medicine and health, marketing, and genetics
An introductory chapter provides a "wide angle" introductory overview and comprehensive survey of mixed data analysis

Blending theory and methodology, this book illustrates concepts via data from different disciplines. Analysis of Mixed Data: Methods & Applications traces important developments, collates basic results, presents terminology and methodologies, and gives an overview of statistical research applications. It is a valuable resource to methodologically interested as well as subject matter-motivated researchers in many disciplines.

About the Authors

Alexander R. de Leon
is Associate Professor in the Department of Mathematics and Statistics at the University of Calgary.  Originally from the Philippines, he obtained his BSc and MSc from the School of Statistics, University of the Philippines.  After a research studentship at Tokyo University of Science, he completed his PhD in Statistics in 2002 at the University of Alberta.  His research interests include methods for analyzing correlated data, multivariate models and distances for mixed discrete and continuous outcomes, pseudo- and composite likelihood methods, copula modeling, assessment of diagnostic tests, and statistical problems in medicine.

Keumhee C. Chough is Professor of Statistics in the Department of Mathematical and Statistical Sciences at the University of Alberta. After completing her BSc in Agriculture from Seoul National University, in Seoul, Korea, she earned her MSc from the University of Manitoba, and her PhD in Statistics from the University of Wisconsin-Madison in 1989.  Since 1996, she has been with the Department of Mathematical and Statistical Sciences, University of Alberta, after stints as Assistant Professor at the University of Iowa (1990-1992) and University of Manitoba (1992-1996). She was also the Director of the Statistics Consulting Center at the University of Iowa (1990-1992).  Her research interests include design and analysis for repeated measures data, missing data methods, high dimensional data analysis methods, multivariate methods, designs for clinical trials, item response data, variable selection methods, and survival analysis. As well, she specializes in such biostatistical methods as small area variation analysis techniques with applications to health care utilization.  She has been a Health Scientist funded through the Alberta Heritage Foundation for Medical Research (1996-2011).  She is a Fellow of the American Statistical Association, the Institute of Health Economics, and the Manitoba Centre for Health Policy.

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ISBN 9781439884713, January 2013, 262pp

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