The Iowa gambling task and Expectancy Valence Model parameters demonstrate measurable test-retest reliability
the verdict
SUPPORTED
the evidence backs this
confidence 81/100
Recent empirical studies confirm that the Iowa Gambling Task and its associated computational parameters, such as expectancy-valence and reinforcement learning metrics, demonstrate acceptable to good test-retest reliability.
Evidence for · 2
Reliability of Decision-Making and Reinforcement Learning Computational Parameters
2021 · cited by 8
This study demonstrates that reinforcement learning and prospect theory model parameters derived from calibrated gambling tasks exhibit good to excellent test-retest reliability.
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More for · 1
Test-retest reliability of the play-or-pass version of the Iowa Gambling Task
2024 · cited by 4
This paper evaluates the play-or-pass version of the Iowa Gambling Task and finds that measures using both traditional scoring and computational modeling demonstrate good test-retest reliability.