Overview

Computational modeling is now ubiquitous in psychology, and researchers who are not modelers may find it increasingly difficult to follow the theoretical developments in their field. This book presents an integrated framework for the development and application of models in psychology and related disciplines. Researchers and students are given the knowledge and tools to interpret models published in their area, as well as to develop, fit, and test their own models. Both the development of models and key features of any model are covered, as are the applications of models in a variety of domains across the behavioural sciences. A number of chapters are devoted to fitting models using maximum likelihood and Bayesian estimation, including fitting hierarchical and mixture models. Model comparison is described as a core philosophy of scientific inference, and the use of models to understand theories and advance scientific discourse is explained.

Full Product Details

Author:   Simon Farrell (University of Western Australia, Perth) ,  Stephan Lewandowsky (University of Bristol)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press
Dimensions:   Width: 17.30cm , Height: 2.30cm , Length: 24.60cm
Weight:   0.970kg
ISBN:  

9781107525610

ISBN 10:   1107525616
Pages:   482
Publication Date:   22 February 2018
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Preface; Part I. Introduction to Modeling: 1. Introduction; 2. From words to models: building a toolkit; Part II. Parameter Estimation: 3. Basic parameter estimation techniques; 4. Maximum likelihood parameter estimation; 5. Combining information from multiple participants; 6. Bayesian parameter estimation: basic concepts; 7. Bayesian parameter estimation: Monte Carlo methods; 8. Bayesian parameter estimation: the JAGS language; 9. Multilevel or hierarchical modeling; Part III. Model Comparison: 10. Model comparison; 11. Bayesian model comparison using Bayes factors; Part IV. Models in Psychology: 12. Using models in psychology; 13. Neural network models; 14. Models of choice response time; 15. Models in neuroscience; Appendix A: Greek symbols; Appendix B: mathematical terminology; References; Index.

Reviews

'I shudder to think about the time I could have saved had this book been available earlier. This educational masterpiece presents classic insights, modern methods, concrete examples, and expert advice; it should be required reading for anybody who seeks to understand human cognition and behavior.' Eric-Jan Wagenmakers, Universiteit van Amsterdam 'This timely book is a must-read for every aspiring student of cognitive modeling. It provides a comprehensive and in-depth coverage of the conceptual and practical foundations of computational cognition, for the beginner and the experienced reader alike. The art of applying all major modeling frameworks, including Bayesian, frequentist, and neural networks, is explained in a most lucid and accessible manner.' Jay Myung, Ohio State University 'An extraordinary achievement: the authors guide the reader from simple ideas about the nature of science to detailed, but lucidly explained, computer models of human behaviour. Associated statistical methods are comprehensively discussed. A pleasure to read.' Philip T. Smith, University of Reading 'Farrell and Lewandowsky have succeeded in their ambition of spanning introductory to cutting-edge material. This book, and a willingness to dive in and learn by doing the exercises provided, is all that undergraduate and graduate students, and even established researchers, need to become a cognitive modeller.' Andrew Heathcote, University of Tasmania, Australia `I shudder to think about the time I could have saved had this book been available earlier. This educational masterpiece presents classic insights, modern methods, concrete examples, and expert advice; it should be required reading for anybody who seeks to understand human cognition and behavior.' Eric-Jan Wagenmakers, Psychological Methods, University of Amsterdam `This timely book is a must-read for every aspiring student of cognitive modeling. It provides a comprehensive and in-depth coverage of the conceptual and practical foundations of computational cognition, for the beginner and the experienced reader alike. The art of applying all major modeling frameworks, including Bayesian, frequentist, and neural networks, is explained in a most lucid and accessible manner.' Jay Myung, Ohio State University `An extraordinary achievement: the authors guide the reader from simple ideas about the nature of science to detailed, but lucidly explained, computer models of human behaviour. Associated statistical methods are comprehensively discussed. A pleasure to read.' Philip T. Smith, University of Reading 'Farrell and Lewandowsky have succeeded in their ambition of spanning introductory to cutting-edge material. This book, and a willingness to dive in and learn by doing the exercises provided, is all that undergraduate and graduate students, and even established researchers, need to become a cognitive modeller.' Andrew Heathcote, University of Tasmania, Australia

Advance praise: 'I shudder to think about the time I could have saved had this book been available earlier. This educational masterpiece presents classic insights, modern methods, concrete examples, and expert advice; it should be required reading for anybody who seeks to understand human cognition and behavior.' Eric-Jan Wagenmakers, Psychological Methods, University of Amsterdam Advance praise: 'This timely book is a must-read for every aspiring student of cognitive modeling. It provides a comprehensive and in-depth coverage of the conceptual and practical foundations of computational cognition, for the beginner and the experienced reader alike. The art of applying all major modeling frameworks, including Bayesian, frequentist, and neural networks, is explained in a most lucid and accessible manner.' Jay Myung, Ohio State University Advance praise: 'An extraordinary achievement: the authors guide the reader from simple ideas about the nature of science to detailed, but lucidly explained, computer models of human behaviour. Associated statistical methods are comprehensively discussed. A pleasure to read.' Philip T. Smith, University of Reading Advance praise: 'Farrell and Lewandowsky have succeeded in their ambition of spanning introductory to cutting-edge material. This book, and a willingness to dive in and learn by doing the exercises provided, is all that undergraduate and graduate students, and even established researchers, need to become a cognitive modeller.' Andrew Heathcote, University of Tasmania, Australia

Author Information

Simon Farrell is professor and an Australian Research Council Future Fellow in the School of Psychology at the University of Western Australia. He uses computational modeling and experiments to understand memory, judgement, choice, and the role of memory in decision-making. He is the co-author of Computational Modeling in Cognition: Principles and Practice (2011) and has published numerous papers on the application of models to psychological data. Simon was Associate Editor of the Journal of Memory and Language (2009–11) and the Quarterly Journal of Experimental Psychology (2011–16). In 2009 Farrell was awarded the Bertelson Award by the European Society for Cognitive Psychology for his outstanding early career contribution to European Cognitive Psychology. Stephan Lewandowsky is a cognitive scientist in the School of Experimental Psychology at the University of Bristol. He was awarded a Discovery Outstanding Researcher Award from the Australian Research Council in 2011 and received a Wolfson Research Fellowship from the Royal Society upon moving to Bristol in 2013. He was appointed a Fellow of the Academy of Social Sciences in 2017. His research examines people's memory and decision-making, with an emphasis on how people update information in memory. He has published over 150 scholarly articles and books, including numerous papers on how people respond to corrections of misinformation and what determines people's acceptance of scientific findings.

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