{Reference Type}: Journal Article
{Title}: Assessing the distortions introduced when calculating d': A simulation approach.
{Author}: Chen Y;Daly HR;Pitt MA;Van Zandt T;
{Journal}: Behav Res Methods
{Volume}: 0
{Issue}: 0
{Year}: 2024 Jul 3
{Factor}: 5.953
{DOI}: 10.3758/s13428-024-02447-8
{Abstract}: The discriminability measure d '  is widely used in psychology to estimate sensitivity independently of response bias. The conventional approach to estimate d '  involves a transformation from the hit rate and the false-alarm rate. When performance is perfect, correction methods must be applied to calculate d '  , but these corrections distort the estimate. In three simulation studies, we show that distortion in d '  estimation can arise from other properties of the experimental design (number of trials, sample size, sample variance, task difficulty) that, when combined with application of the correction method, make d '  distortion in any specific experiment design complex and can mislead statistical inference in the worst cases (Type I and Type II errors). To address this problem, we propose that researchers simulate d '  estimation to explore the impact of design choices, given anticipated or observed data. An R Shiny application is introduced that estimates d '  distortion, providing researchers the means to identify distortion and take steps to minimize its impact.