eCite Digital Repository

The Expectancy Valence Model: Can it identify individual performance deficits on the Iowa gambling task?

Citation

Humphries, MA and Wotherspoon, SJ and Bruno, RB and Karpievitch, YV, The Expectancy Valence Model: Can it identify individual performance deficits on the Iowa gambling task?, 2013 Australasian Mathematical Psychology Conference Sydney, New South Wales, Australia, 15-17 February 2013, Sydney, New South Wales, pp. 27. (2013) [Conference Extract]


Preview
PDF (program, abstracts)
Pending copyright assessment - Request a copy
1Mb
  

Abstract

The Expectancy Valence Model (EVM) is currently being used in numerous studies to estimate neurological deficits in decision making on the Iowa Gambling Task (IGT). This is despite a growing body of evidence that the EVM may not be providing accurate estimates. Using Bayesian estimation techniques of the EVM with random effects, we show the EVM does not provide clear information about the neurological processes underlying deficient abilities at the individual level. Due to bi-modal and non-linear parameter distributions and due to distributions on the boundary of parameter space, parameter estimates that are obtained using the EVM are unreliable and/or have little psychological significance. A multiple run version of the IGT was also trialled in hopes of decreasing the variability of parameter estimates, but no improvement in accuracy was observed. It is therefore found that the EVM should not be used to model performance on the IGT.

Item Details

Item Type:Conference Extract
Research Division:Mathematical Sciences
Research Group:Statistics
Research Field:Applied Statistics
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in the Mathematical Sciences
Author:Humphries, MA (Mrs Melissa Humphries)
Author:Wotherspoon, SJ (Dr Simon Wotherspoon)
Author:Bruno, RB (Associate Professor Raimondo Bruno)
Author:Karpievitch, YV (Dr Yuliya Karpievitch)
ID Code:83522
Year Published:2013
Deposited By:Mathematics and Physics
Deposited On:2013-03-15
Last Modified:2013-06-27
Downloads:3 View Download Statistics

Repository Staff Only: item control page