Statistical Meta-Analysis with Applications

This book combines the authors' experiences on the topic and brings out a wealth of new information relevant to the study of meta-analysis. Applications ranging from business to education to environment to health sciences in both univariate and multivariate cases are presented alongside and subservient to theory. The treatment of the common mean of univariate normal populations, tests of homogeneity, one-way random effects model, categorical data, recovery of inter-block information, and combination of polls is entirely new. A special feature includes the incorporation of detailed discussions on the computational aspects and related software to carry out statistical meta-analysis in practice. Most of the methods described can be understood and applied with a solid master's level background in statistics. Practitioners will benefit from the book owing to a host of worked-out examples from numerous and various contexts.

JOACHIM HARTUNG, PhD, is Professor in the Department of Statistics at the Dortmund University of Technology, Germany. He has published several books and two dozen journal articles in the field of statistics. GUIDO KNAPP, PhD, is Assistant Professor in the Department of Statistics at the Dortmund University of Technology, Germany. Dr. Knapp's areas of research interest include variance component models, error components regression models, meta-analysis, and flexible design in clinical trials. BIMAL K. SINHA, PhD, is Presidential Research Professor of Statistics in the Department of Mathematics and Statistics at the University of Maryland at Baltimore County (UMBC). A Fellow of both the Institute of Mathematical Statistics and the American Statistical Association, Dr. Sinha's research specializes in the areas of multivariate analysis, mixed linear models, decision theory, robustness, and environmental statistics.