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- Title
Analyzing recognition performance with sparse data.
- Authors
Ching-Fan Sheu; Yuh-Shiow Lee; Pei-Ying Shih
- Abstract
Experiments in which recognition performance is measured sometimes involve only a small number of observations per subject, rendering d' analysis unreliable (Schooler & Shiffrin, 2005). Here, we introduce, in signal detection models, subject-specific random variables to account for heterogeneous hit and false alarm rates among individuals. Population d' effects for comparing groups are estimated, in this approach, by pooling information from a sample of subjects across experimental conditions. The method is validated by a simulation study and is illustrated with an analysis of the effect of neutral and emotional words on recognition performance, employing the emotional Stroop task (Lee & Shih, 2007).
- Subjects
PERFORMANCE; RECOGNITION (Psychology); MEASUREMENT; SIGNAL detection (Psychology); BEHAVIORAL research
- Publication
Behavior Research Methods, 2008, Vol 40, Issue 3, p722
- ISSN
1554-351X
- Publication type
Article
- DOI
10.3758/BRM.40.3.722