Inferring choice criteria with mixture IRT models: A demonstration using ad hoc and goal-derived categories

Whether it pertains to the foods to buy when one is on a diet, the items to take along to the beach on one’s day off or (perish the thought) the belongings to save from one’s burning house, choice is ubiquitous. We aim to determine from choices the criteria individuals use when they select objects from among a set of candidates. In order to do so we employ a mixture IRT (item-response theory) model that capitalizes on the insights that objects are chosen more often the better they meet the choice criteria and that the use of different criteria is reflected in inter-individual selection differences. The model is found to account for the inter-individual selection differences for 10 ad hoc and goal-derived categories. Its parameters can be related to selection criteria that are frequently thought of in the context of these categories. These results suggest that mixture IRT models allow one to infer from mere choice behavior the criteria individuals used to select/discard objects. Potential applications of mixture IRT models in other judgment and decision making contexts are discussed

When cheating is an honest mistake

Dishonesty is an intriguing phenomenon, studied extensively across various disciplines due to its impact on people’s lives as well as society in general. To examine dishonesty in a controlled setting, researchers have developed a number of experimental paradigms. One of the most popular approaches in this regard, is the matrix task, in which participants receive matrices wherein they have to find two numbers that sum to 10 (e.g., 4.81 and 5.19), under time pressure. In a next phase, participants need to report how many matrices they had solved correctly, allowing them the opportunity to cheat by exaggerating their performance in order to get a larger reward. Here, we argue, both on theoretical and empirical grounds, that the matrix task is ill-suited to study dishonest behavior, primarily because it conflates cheating with honest mistakes. We therefore recommend researchers to use different paradigms to examine dishonesty, and treat (previous) findings based on the matrix task with due caution