Near‐miss events, which occur when failure is avoided by chance, can lead to subsequent
risky decisions due to base‐rate neglect. According to construal level theory, a lower level …

py-irt is a Python library for fitting Bayesian item response theory (IRT) models. At present,
there is no Python package for fitting large-scale IRT models. py-irt estimates latent traits of …

A persistently pressing issue identified in the decision‐making literature is that people not
only fail to recognize the risks entailed in a near‐loss event but also subsequently engage in …

Many disasters generate dread and fear among the directly affected population and often
also among those who believe they may be subsequently affected by the current or a similar …

The classic normative model for intertemporal preferences uses a constant discount rate, but
behavioral experiments have shown that people do not tend to make choices consistent with …

Near-miss events are a topic of increasing interest, motivated by a growing body of literature
showing that these events are often not perceived as a sign of warning, but may lead to …

This chapter focuses on responses to near‐miss experiences in a cyber environment
involving negative consequences (eg loss of data, credit card fraud) that could have …

Near-miss experiences have been identified as a contributing factor in responses to risk of
disaster events. Previous research suggested that different near-miss events could lead …