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Adelaide Research and Scholarship
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Schools and Disciplines
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School of Psychology
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Psychology Publications
Permanent link to this item:
http://hdl.handle.net/2440/23023
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| Type: | Article |
| Title: | Global model analysis by parameter space partitioning |
| Author: | Pitt, M. A.
Kim, Woojae
Navarro, Daniel Joseph
Myung, J. I. |
| Citation: | Psychological Review, 2006; 113 (1):57-83 |
| Publisher: | American Psychological Association |
| Issue Date: | 2006 |
| ISSN: | 0033-295X |
| School/Discipline: | Psychology
School of Chemistry and Physics |
Statement of
Responsibility: | Mark A. Pitt, Woojae Kim, Daniel J. Navarro, and Jay I. Myung |
| Abstract: | To model behavior, scientists need to know how models behave. This means learning what other behaviors
a model can produce besides the one generated by participants in an experiment. This is a difficult problem
because of the complexity of psychological models (e.g., their many parameters) and because the behavioral
precision of models (e.g., interval-scale performance) often mismatches their testable precision in experiments,
where qualitative, ordinal predictions are the norm. Parameter space partitioning is a solution that evaluates
model performance at a qualitative level. There exists a partition on the model’s parameter space that divides
it into regions that correspond to each data pattern. Three application examples demonstrate its potential and
versatility for studying the global behavior of psychological models. |
| Keywords: | Model comparison; model complexity; MCMC; connectionist modeling |
| Description: | Copyright 2006 American Psychological Association
This article may not exactly replicate the final version published in the APA journal. It is not the copy of record. |
| RMID: | 0020060144 |
| DOI: | 10.1037/0033-295X.113.1.57 |
| Published version: | http://www.apa.org/journals/rev/homepage.html |
Links to content
(authorised users): | Check full text options |
| Appears in Collections: | Psychology Publications
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| View citing articles in: | Google Scholar
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