Designed to provide researchers clear and informative insight into techniques of meta-analysis, the Third Edition of Methods of Meta-Analysis: Correcting Error and Bias in Research Findings is the most comprehensive text on meta-analysis available today. It is the only book that presents a full and usable treatment of the role of study artifacts in distorting study results, as well as methods for correcting results for such biases and errors.
Meta-analysis is arguably the most important methodological innovation in the last thirty-five years, due to its immense impact on the development of cumulative knowledge and professional practice. This text, now in its updated Third Edition, has been revised to cover the newest developments in meta-analysis methods, evaluation, correction, and more. This reader-friendly book is the definitive resource on meta-analysis.
Arvustused
"This text is the primary source text for psychometric meta-analysis methodsThis is the only comprehensive resource available for researchers interested in conducting psychometric meta-analysis methods. Another strength of the text is the inclusion of substantive examples from the field of IO psychology, which always helps with student comprehension." -- Emily E. Tanner-Smith, Vanderbilt University "The key strength of the book is the complete and thorough coverage of psychometric meta-analysis. This technique is not covered in any other meta-analysis text, and is a major contribution to the literatureThe meta-analysis field needs to find ways to integrate Hunter and Schmidts methods into current meta-analysis practice." -- Terri D. Pigott, Loyola University of Chicago "This is an important textIt is the only book that presents adequate coverage of psychometric meta-analysisit is an invaluable resource for anyone involved in meta-analytic studies." -- Steven Pulos, University of Northern Colorado
PART I: INTRODUCTION TO META-ANALYSIS
1. Integrating Research Finding Across Studies
2. Study Artifacts and Their Impact on Study Outcomes
PART II: META-ANALYSIS OF CORRELATIONS
3. Meta-Analysis of Correlations Corrected Individually for Artifacts
4. Meta-Analysis of Correlations Using Artifact Distributions
5. Technical Questions In Meta-Analysis of Correlations
PART III: META-ANALYSIS OF EXPERIMENTAL EFFECTS AND OTHER DICHOTOMOUS
COMPARISONS
6. Treatment Effects: Experimental Artifacts and Their Impact
7. Meta-Analysis Methods for d Values
8. Technical Questions in Meta-Analysis of d Values
PART IV: GENERAL ISSUES IN META-ANALYSIS
9. General Technical Issues in Meta-Analysis
10. Cumulation of Findings Within Studies
11. Different Meta-Analysis Methods and Related Software
12. Locating, Evaluating, Selecting, and Coding Studies and Presentation of
Meta-Analysis Results
13. Availability Bias, Source Bias, and Publication Bias in Meta-Analysis
14. Summary of Psychometric Meta-Analysis
Frank L. Schmidt is the Gary F. Fethke Leadership Professor Emeritus in the Department of Management and Organization in the Tippie College of Business at the University of Iowa. He received his Ph.D. in industrial/organizational psychology from Purdue University and has been on the faculties of Michigan State and George Washington Universities. He has authored or coauthored seven books and nearly 200 articles and book chapters on measurement, statistics, research methods, individual differences, and personnel selection. He headed a research program in the U.S. Office of Personnel Management in Washington, D.C., for 11 years, during which time he published numerous research studies in personnel psychology, primarily with John Hunter. Their research on the generalizability of employment selection method validities led to the development of the meta-analysis methods presented in this book. Professor Schmidt has received the Distinguished Scientific Award for Contributions to Applied Psychology from the American Psychological Association (APA) (jointly with John Hunter) and the Distinguished Scientific Contributions Award from the Society for Industrial/Organizational Psychology (SIOP) (also jointly with John Hunter). He has also received the Ingram Olkin Award and the Frederick Mosteller Award, both for contributions to meta-analysis methodology; the Scientific Award for Applications of Psychology from the Association for Psychological Science (APS); the Gold Medal Lifetime Achievement award from the APA Foundation; the Distinguished Career Award for Contributions to Human Resources, and the Distinguished Career Achievement Award for Contributions to Research Methods, both from the Academy of Management. He is a Fellow of the APA, the Association for Psychological Science, and SIOP, and is past president of Division 5 (Measurement, Statistics, & Evaluation) of the APA.
John E. (Jack) Hunter (1939--2002) was a professor in the Department of Psychology at Michigan State University. He received his Ph.D. in quantitative psychology from the University of Illinois. Jack coauthored four books and authored or coauthored over 200 articles and book chapters on a wide variety of methodological topics, including confirmatory and exploratory factor analysis, measurement theory and methods, statistics, and research methods. He also published numerous research articles on such substantive topics as intelligence, attitude change, the relationship between attitudes and behavior, validity generalization, differential validity/selection fairness, and selection utility. Much of his research on attitudes was in the field of communications, and the American Communications Association named a research award in his honor. Professor Hunter received the Distinguished Scientific Award for Contributions to Applied Psychology from the American Psychological Association (APA) (jointly with Frank Schmidt) and the Distinguished Scientific Contributions Award from the Society for Industrial/Organizational Psychology (SIOP) (also jointly with Frank Schmidt). He was a Fellow of APA, APS, and SIOP, and was a past president of the Midwestern Society for Multivariate Experimental Psychology. For the story of Jacks life, see Schmidt (2003).
