[Online] Effects of Varying Evidence Level on Recognition Accuracy

Background

Previous studies have found that regardless of the condition, the more confident an individual is, and the faster their responses are, and the more accurate their identification is. This research aims to find out if the same effects can be found in two-alternative forced choice (2AFC) tasks where the relative and absolute levels of difference between choice alternatives is manipulated. Although there exists many models that aim to explain the relationship between confidence, response time and accuracy in decision making (e.g., Ratcliff & Starns, 2009; Voskuilen & Ratcliff, 2015, Wixted & Mickes, 2014), those models were inadequate to provide a unified account that relates confidence and RT to the accuracy of choices in recognition. Therefore we proposed a new model, the Multiple Threshold Race model (MTR) that has the potential to provide such unified account.

Research Questions / Hypotheses

This research aims to find out whether manipulating the relative and absolute differences in choice pairs produced distinct response patterns in 2AFC tasks.

Participants

A total of 41 REP participants completed the study.

Methods

In this experiment participants completed several cycles of a computer-based visual recognition task. In each of the task, participants were presented with series of pairs of squares with each consisting of different coloured (orange or blue) flashing pixels. Some squares contained more orange coloured pixels while some contained more blue coloured pixels. Some pairs of squares were easy to tell the difference apart because of the larger difference in the proportions of colours; while some were harder to tell due to smaller difference; some were even impossible to tell as there was absolutely no difference between them. Participants were required to identify whether one of the squares in the pair contained higher proportion of a certain colour.

Results

Preliminary analysis showed that increasing the absolute level of evidence in equal-evidence condition decreases RTs and increases confidence. Also, increasing the relative level of evidence in unequal-evidence condition increases accuracy, decreases RTs and increases confidence.

Implications

It is possible that the Multiple Threshold Race model may struggle in fitting this type of data, which may distinguish it from other confidence models.