A mixed-effects expectancy-valence model for the Iowa gambling task

Chung Ping Cheng, Ching Fan Sheu, Nai Shing Yen

研究成果: Article同行評審

7 引文 斯高帕斯(Scopus)

摘要

The Iowa gambling task (IGT; Bechara, Damasio, Damasio, & Anderson, 1994) was developed to simulate real-life decision making under uncertainty. The task has been widely used to examine possible neurocognitive deficits in normal and clinical populations. Busemeyer and Stout (2002) proposed the expectancy-valence (EV) model to explicitly account for individual participants? repeated choices in the IGT. Parameters of the EV model presumably measure different psychological processes that underlie performance on the task, and their values may be used to differentiate individuals across different populations. In the present article, the EV model is extended to include both fixed effects and subject-specific random effects. The mixed-effects EV model fits the nested structure of observations in the IGT naturally and provides a unified procedure for parameter estimation and comparisons among groups of populations. We illustrate the utility of the mixed-effects approach with an analysis of gender differences using a real data set. A simulation study was conducted to verify the advantages of this approach.

原文English
頁(從 - 到)657-663
頁數7
期刊Behavior Research Methods
41
發行號3
DOIs
出版狀態Published - 2009 8月

All Science Journal Classification (ASJC) codes

  • 實驗與認知心理學
  • 發展與教育心理學
  • 藝術與人文(雜項)
  • 心理學(雜項)
  • 心理學(全部)

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