A solution to the pervasive problem of response bias in self-reports.

Self-reports are used ubiquitously to probe people's thoughts, feelings, and behaviors and inform medical decisions, enterprise operations, and government policy and legislation. Despite their pervasive use, self-report measures such as Likert scales have a profound problem: Standard analytic approaches do not control for the confounding effects of idiosyncratic response biases. Here, we present a model-based solution to this problem.