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Research and Markets: Bias and Causation: Models and Judgment for Valid Comparisons(M2 PressWIRE Via Acquire Media NewsEdge) Dublin - Research and Markets (http://www.researchandmarkets.com/research/a65060/bias_and_causation) has announced the addition of John Wiley and Sons Ltd's new report "Bias and Causation: Models and Judgment for Valid Comparisons" to their offering. A one-of-a-kind resource on identifying and dealing with bias in statistical research on causal effects Do cell phones cause cancer? Can a new curriculum increase student achievement? Determining what the real causes of such problems are, and how powerful their effects may be, are central issues in research across various fields of study. Some researchers are highly skeptical of drawing causal conclusions except in tightly controlled randomized experiments, while others discount the threats posed by different sources of bias, even in less rigorous observational studies. Bias and Causation presents a complete treatment of the subject, organizing and clarifying the diverse types of biases into a conceptual framework. The book treats various sources of bias in comparative studiesboth randomized and observationaland offers guidance on how they should be addressed by researchers. Utilizing a relatively simple mathematical approach, the author develops a theory of bias that outlines the essential nature of the problem and identifies the various sources of bias that are encountered in modern research. The book begins with an introduction to the study of causal inference and the related concepts and terminology. Next, an overview is provided of the methodological issues at the core of the difficulties posed by bias. Subsequent chapters explain the concepts of selection bias, confounding, intermediate causal factors, and information bias along with the distortion of a causal effect that can result when the exposure and/or the outcome is measured with error. The book concludes with a new classification of twenty general sources of bias and practical advice on how mathematical modeling and expert judgment can be combined to achieve the most credible causal conclusions. Throughout the book, examples from the fields of medicine, public policy, and education are incorporated into the presentation of various topics. In addition, six detailed case studies illustrate concrete examples of the significance of biases in everyday research. Requiring only a basic understanding of statistics and probability theory, Bias and Causation is an excellent supplement for courses on research methods and applied statistics at the upper-undergraduate and graduate level. It is also a valuable reference for practicing researchers and methodologists in various fields of study who work with statistical data. Authors Bio: Herbert I. Weisberg. PhD, is founder and President of Correlation Research Inc., a consulting firm that specializes in the application of statistics to various business and legal issues. Dr. Weisberg has over forty years of statistical consulting experience and has published numerous articles related to bias assessment and reduction. Key Topics Covered: Preface. 1. What Is Bias? Guidepost 1. 2. Causality and Comparative Studies. Guidepost 2. 3. Estimating Causal Effects. Guidepost 3. 4. Varieties of Bias. Guidepost 4. 5. Selection Bias. Guidepost 5. 6. Confounding: An Enigma? Guidepost 6. 7. Confounding: Essence, Correction, and Detection. Guidepost 7. 8. Intermediate Causal Factors. Guidepost 8. 9. Information Bias. Guidepost 9. 10. Sources of Bias. Guidepost 10. 11. Contending with Bias. Reviews: "A consultant who specializes in applying statistics to various business and legal issues, Weisberg explains approaches to bias and causal inference, a realm statisticians have avoided until recently because it requires intuitive skills beyond the pale of mathematics. He writes for practicing researchers and methodologists and for students with a reasonably solid grounding in basic statistics and research methods." (SciTech Book News, December 2010) To view the reports full table of contents and for more information visit http://www.researchandmarkets.com/research/a65060/bias_and_causation CONTACT: Research and Markets Laura Wood, Senior Manager, [email protected] U.S. Fax: 646-607-1907 Fax (outside U.S.): +353-1-481-1716 ((M2 Communications disclaims all liability for information provided within M2 PressWIRE. Data supplied by named party/parties. Further information on M2 PressWIRE can be obtained at http://www.presswire.net on the world wide web. Inquiries to [email protected])). (c) 2011 M2 COMMUNICATIONS |