The use of mixed models in a modified Iowa Gambling Task and a prisoner’s dilemma game

dc.contributor.authorStockard, Jean
dc.contributor.authorPeters, Ellen
dc.contributor.authorO'Brien, Robert
dc.date.accessioned2017-01-26T18:44:41Z
dc.date.available2017-01-26T18:44:41Z
dc.date.issued2007-02
dc.description14 pagesen_US
dc.description.abstractResearchers in the decision making tradition usually analyze multiple decisions within experiments by aggregating choices across individuals and using the individual subject as the unit of analysis. This approach can mask important variations and patterns within the data. Specifically, it ignores variations in decisions across a task or game and possible influences of characteristics of the subject or the experiment on these variations. We demonstrate, by reanalyzing data from two previously published articles, how a mixed model analysis addresses these limitations. Our results, with a modified Iowa gambling task and a prisoner’s dilemma game, illustrate the ways in which such an analysis can test hypotheses not possible with other techniques, is more parsimonious, and is more likely to be faithful to theoretical models.en_US
dc.identifier.citationStockard, J., O'Brien, R. M., & Peters, E. (2007). The use of mixed models in a modified Iowa Gambling Task and a prisoner's dilemma game. Judgment and Decision Making, 2, 9-22 Retrieved from http://journal.sjdm.org/vol2.1.htmen_US
dc.identifier.urihttps://hdl.handle.net/1794/22077
dc.language.isoen_USen_US
dc.publisherSociety for Judgment and Decision Making,en_US
dc.rightsCreative Commons BY-NC-ND 4.0-USen_US
dc.subjectDecision makingen_US
dc.subjectWithin-subject and between-subject designsen_US
dc.subjectMixed modelsen_US
dc.subjectIndividual differencesen_US
dc.subjectStatisticsen_US
dc.subjectRepeated measuresen_US
dc.subjectMixed modelsen_US
dc.subjectIowa Gambling Tasken_US
dc.subjectPrisoner's dilemmaen_US
dc.titleThe use of mixed models in a modified Iowa Gambling Task and a prisoner’s dilemma gameen_US
dc.typeArticleen_US

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