Neuroeconomics: Chapter 4. Estimation and Testing of Computational Psychological Models Book PDF, ePub eBook

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Book Descriptions:
This chapter provides a brief overview of all the steps of computational modeling and illustrates their use in cognitive and decision neuroscience. The chapter starts with a simple example model developed for a popular “decision from experience” type of task. Second, the chapter discusses the important issue concerning analysis of group versus individual data. Third, methods for estimating model parameters are presented, which includes least squares, maximum likelihood, Bayesian estimation, and hierarchical Bayesian estimation. Fourth methods for model comparison are discussed such as R-square, chi-square, Akaike information criterion, Bayesian information criterion, generalization criterion, and cross validation. Finally the importance of using these methods are illustrated with an example model based fMRI application.

Neuroeconomics: Chapter 4. Estimation and Testing of Computational Psychological Models by Jerome R. Busemeyer, Adele Diederich

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