City Research Online

Abstract

Maximum Likelihood (ML) estimators such as QUEST+ allow complex psychophysical measurements to be made more quickly and precisely than traditional staircase techniques. They could therefore be useful for quantifying sensory function in populations with limited attention spans, such as children. To test this, the present study empirically evaluated the performance of an ML estimator (QUEST+) versus a traditional Up-Down Weighted Staircase in children and adults. Seventy-one children (4.7–14.7 years) and 43 adults (18.1–29.6 years) completed a typical psychophysical procedure: Contrast Sensitivity Function (CSF) determination. Some participants were tested twice with the same method (QUEST+ or Staircase), allowing test-retest repeatability to be quantified. Others were tested once each with either method (QUEST+ and Staircase), allowing accuracy to be quantified. The results showed that QUEST+ was more efficient: In both children and adults, approximately half the number of ML trials were required to attain comparable levels of accuracy and reliability as a traditional Staircase paradigm, and plausible CSF estimates could be made in even the youngest children. The ML procedure was also as robust as the Staircase to lapses in concentration, and its performance did not depend on prespecifying correct model priors. The results show that ML estimators could greatly improve our ability to study sensory processes and detect impairments in children, although important practical considerations for-and-against their use are discussed.

Publication Type:	Article
Additional Information:	Copyright 2019 The Authors This work is licensed under a Creative Commons Attribution 4.0 International License.
Publisher Keywords:	11 Medical and Health Sciences, 17 Psychology and Cognitive Sciences
Subjects:	R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Departments:	School of Health & Psychological Sciences > Optometry & Visual Sciences
SWORD Depositor:	Symplectic Administrator

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