A Friendly Introduction to Numerical Analysis, 1st Edition, Brian Bradie, ISBN-10: 0130130540, ISBN-13: 9780130130549, PEARSON, ISM
Introduction to Regression Analysis
Introduction to Economic Analysis
A Short Introduction to Structural Analysis
New findings on unconscious versus conscious thought in decision making: additional empirical data and meta-analysis
Introduction To Spss - Opening Data File and Descriptive Analysis
The Good, the Bad, and the Unknown About Telecommuting: Meta- Analysis of Psychological Mediators and Individual Consequences
An Introduction to Regression Analysis
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Introduction to Econometrics Stock 2rd Edition Solutions Manual
A superb combination of lucid prose and informative graphics, written by four of the world’sleading experts on all aspects of meta-analysis. Borenstein, Hedges, Higgins, and Rothsteinprovide a refreshing departure from cookbook approaches with their clear explanations ofthe what and why of meta-analysis. The book is ideal as a course textbook or for self-study.My students, who used pre-publication versions of some of the chapters, raved about theclarity of the explanations and examples. David Rindskopf, Distinguished Professor of Educational Psychology, City University of New York, Graduate School and University Center, & Editor of the Journal of Educational and Behavioral Statistics.
The approach taken by Introduction to Meta-analysis is intended to be primarily conceptual,and it is amazingly successful at achieving that goal. The reader can comfortably skip theformulas and still understand their application and underlying motivation. For the morestatistically sophisticated reader, the relevant formulas and worked examples provide a superbpractical guide to performing a meta-analysis. The book provides an eclectic mix of examplesfrom education, social science, biomedical studies, and even ecology. For anyone consideringleading a course in meta-analysis, or pursuing self-directed study, Introduction toMeta-analysis would be a clear first choice. Jesse A. Berlin, ScD
Introduction to Meta-Analysis is an excellent resource for novices and experts alike. The bookprovides a clear and comprehensive presentation of all basic and most advanced approachesto meta-analysis. This book will be referenced for decades. Michael A. McDaniel, Professor of Human Resources and Organizational Behavior, Virginia Commonwealth University
Meta-analysis is becoming more and more important in medical research. In my current job I am working on two projects where I am constructing meta-analyses. The pioneering book on this topic was the book by Hedges and Olkin which was the first to put statistical rigor to research synthesis which had previously been done using very ad hoc methods. I have in the past had experience with using published p-values for combination in meta-analysis. It has been more than twenty years since that book came out. You can look a my listmania on meta-analysis to see the various books thyat are currently on the market. Many are theoretical but do not give a good feel for applications. Various approaches have been proposed. There are texts on Bayesian meta-analyse and meta-analyses based on the profile likelihood approach. Some cover p-value combination tests. Some cover special topics such as effect size estimation, mixed modeling approaches.
This book is introductory and is... read more
Introduction to Meta-Analysis (Statistics in Practice)
The book Introduction to Meta-Analysis by Dr. Borenstein, is great book. This may be surprising for a statistic book, but the authors make the process of conducting a meta-analysis very understandable. They have all the formulas, will indexed, in a logical order and explain where the formulas came from. They then work simple examples that are easy to follow. The book gets into more meat in the meta regression area and further clarifies how to leverage the meta-analysis to understand subgroups. I also bought the software Comprehensive Meta-analysis that goes with the book. I plan to buy Dr. Borenstein's next book, which I assume is more advanced.
I'm new to the topic, and found this an invaluable resource. It's very well written, possibly the clearest statistics text I've ever read. Lots of worked examples as well as online software resources to help you. I feel like I could do a meta-analysis today after one read-through.
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