A Two-component circular regression model for repeated measures auditory localization data

Garnett P. McMillan, Timothy E. Hanson, Gabrielle Saunders, Frederick Gallun

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Auditory localization experiments are conducted to evaluate human ability to locate the position of a source of sound, and to determine how population characteristics might affect this ability. These experiments generate data that are circular, bimodal and repeated, and have hypothesized symmetry patterns that should be included and tested within the modelling framework. We propose a two-part mixture of wrapped Cauchy densities for these bimodal angular data, with random effects to model correlation between repeated measures. The effects of signal position and types of symmetry in the signal response around the circle are modelled by using circular B-splines. The model is used to investigate the effects of age and hearing impairment on the ability to localize a low frequency signal. Published 2013. This article is a US Government work and is in the public domain in the USA.

Original languageEnglish (US)
Pages (from-to)515-534
Number of pages20
JournalJournal of the Royal Statistical Society. Series C: Applied Statistics
Volume62
Issue number4
DOIs
StatePublished - Aug 2013

Fingerprint

Repeated Measures
Regression Model
Bimodal
Symmetry
B-spline
Random Effects
Cauchy
Experiment
Low Frequency
Circle
Evaluate
Modeling
Model
Repeated measures
Localization
Regression model

Keywords

  • Angular regression
  • B-splines
  • Bimodal data
  • Sound localization
  • Symmetry models

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

A Two-component circular regression model for repeated measures auditory localization data. / McMillan, Garnett P.; Hanson, Timothy E.; Saunders, Gabrielle; Gallun, Frederick.

In: Journal of the Royal Statistical Society. Series C: Applied Statistics, Vol. 62, No. 4, 08.2013, p. 515-534.

Research output: Contribution to journalArticle

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