- Category: Research Projects
- Published on Saturday, 24 December 2011 10:01
- Written by Richard D. Morey
In recognition memory experiments, participants are given a list of words to remember. They are then presented with another list of words and asked whether each was seen on the previous list, or is new. The most common model used to analyze data from the recognition memory paradigm is signal detection theory (Green & Swets, 1966). However, standard analyses are flawed by aggregation bias. My colleagues and I have developed hierarchical Bayesian models which are not subject to aggregation bias, allowing for accurate analyses of recognition memory data.