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Analysis of variance is the backbone of experimental research. This book is a clear and straightforward guide to how to do the analyses, with an emphasis on how to interpret statistical results and translate them into prose that will clearly tell the audience what the data are saying. There are plenty of end-of-chapter practice problems, all with suggested answers. Life in the laboratory doesn't always follow the script, so both new and established techniques are presented for coping with non-standard situations. Because data analysis is not a closed subject, pros and cons are presented for various options. The final chapter is the first elementary presentation of functional measurement, a methodology built upon analysis of variance. Initially developed by Norman H Anderson, functional measurement (also known as information integration theory) offers a powerful technology for studying cognitive processes. The accompanying CD contains analysis of variance software that is easy to use (really!), with an interface that greets the user with appropriate requests. In addition to programs for standard analyses, the software includes several specialized routines that have heretofore been presented only in journals. This guide will be an important resource for students and professionals in the social, behavioural and neurosciences.
Ward Edwards is well known as the father of behavioral decision
making. In his 1954 Psychological Bulletin paper on decision
making, he brought psychological ideas into what had been the
province of economists. His influence in this realm is so pervasive
that the Nobel committee was able to trace a direct path from
Edwards's work to Daniel Kahneman's 2002 Prize for prospect theory.
In a 1963 Psychological Review paper, Edwards brought Bayesian
statistics to the attention of psychologists, who have continued to
proliferate Bayesian ideas, underscoring the importance of the
perspective. In a 1962 IEEE paper, Edwards foresaw how the world of
intelligence gathering and analysis could by transformed by systems
in which humans provided (subjective) probabilities and machines
provided computational power. He also showed, in a 1986 book
written with Detlof von Winterfeldt, how multiattribute utility
analysis could help real-world decision makers generate
satisfactory solutions to complex problems.
*Comprehensive, accessible text, updated: 40% new material includes a new chapter on multilevel IRT models, new material on loglinear models, and more. *Shows how to apply IRT by using common datasets across chapters. *Companion website provides datasets, software links, and additional resources. *Works through the examples using both free and commercially available software programs. *Of particular interest in the U.S., the U.K., Scandinavia, the Netherlands, Germany, China, and Korea.
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