A Hierarchical Bayesian IRT Analysis of Children’s Risk Propensity

The Children’s Risk Utility Measure (CRUM) is an interactive, modified version of the Balloon Analogue Risk Task (BART) that is appropriate for young children. This paper utilizes a Bayesian IRT model (an extension of logistic regression) to examine the impact of subject-level characteristics (age, working memory, inhibitory control) and trial-level characteristics (e.g. block, order, etc.) on the performance of children ages 3-6 years on the CRUM. The Bayesian model is especially helpful when performing IRT models–which have many parameters–on small data sets. The order of the trials was not associated with lower difficulty, indicating that children’s performance remained steady as the task went on. Working memory performance was negatively associated with children’s latent CRUM performance, while high scores on an inhibitory control task were positively related to child’s latent CRUM performance. Age and the interaction of age with working memory performance were both negligible effects. The IRT model was an effective way to estimate latent CRUM performance.