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A joint modeling approach for reaction time and accuracy in psycholinguistic experiments

Tom Loeys UGent, Yves Rosseel UGent and Kristof Baten UGent (2010) 18th annual meeting of the Belgian statistical society, Abstracts.
abstract
In the psycholinguistic literature, reaction times and accuracy can be analyzed separately using mixed (logistic) effects models with crossed random effects for item and subject. Given the potential correlation between these two outcomes, a joint model for the reaction time and accuracy may provide further insight. In this paper, a Bayesian hierarchical framework is proposed that allows estimation of the correlation between time intensity and difficulty at the item level, and between speed and ability at the subject level. The framework is shown to be flexible in that reaction times can follow a (log-) normal or (shifted) Weibull distribution. A simulation study reveals the reduction in bias gains possible when using joint models, and an analysis of an example from a Dutch–English word recognition study illustrates the proposed method.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
psycholinguistic experiment, reaction time, Bayesian estimation, joint modeling, SPEED, WINBUGS, FRAMEWORK, LANGUAGE, SIGNAL-DETECTION, RESPONSE-TIME, FIXED-EFFECT FALLACY
in
18th annual meeting of the Belgian statistical society, Abstracts
conference name
18th Annual Meeting of the Belgian Statistical Society (BSS - 2010)
conference location
Spa, Belgium
conference start
2010-10-14
conference end
2010-10-15
language
English
UGent publication?
yes
classification
C3
copyright statement
I have retained and own the full copyright for this publication
id
2006028
handle
http://hdl.handle.net/1854/LU-2006028
date created
2012-01-27 11:13:49
date last changed
2016-12-19 15:37:42
@inproceedings{2006028,
  abstract     = {In the psycholinguistic literature, reaction times and accuracy can be analyzed separately using mixed (logistic) effects models with crossed random effects for item and subject. Given the potential correlation between these two outcomes, a joint model for the reaction time and accuracy may provide further insight. In this paper, a Bayesian hierarchical framework is proposed that allows estimation of the correlation between time intensity and difficulty at the item level, and between speed and ability at the subject level. The framework is shown to be flexible in that reaction times can follow a (log-) normal or (shifted) Weibull distribution. A simulation study reveals the reduction in bias gains possible when using joint models, and an analysis of an example from a Dutch--English word recognition study illustrates the proposed method.},
  author       = {Loeys, Tom and Rosseel, Yves and Baten, Kristof},
  booktitle    = {18th annual meeting of the Belgian statistical society, Abstracts},
  keyword      = {psycholinguistic experiment,reaction time,Bayesian estimation,joint modeling,SPEED,WINBUGS,FRAMEWORK,LANGUAGE,SIGNAL-DETECTION,RESPONSE-TIME,FIXED-EFFECT FALLACY},
  language     = {eng},
  location     = {Spa, Belgium},
  title        = {A joint modeling approach for reaction time and accuracy in psycholinguistic experiments},
  year         = {2010},
}

Chicago
Loeys, Tom, Yves Rosseel, and Kristof Baten. 2010. “A Joint Modeling Approach for Reaction Time and Accuracy in Psycholinguistic Experiments.” In 18th Annual Meeting of the Belgian Statistical Society, Abstracts.
APA
Loeys, T., Rosseel, Y., & Baten, K. (2010). A joint modeling approach for reaction time and accuracy in psycholinguistic experiments. 18th annual meeting of the Belgian statistical society, Abstracts. Presented at the 18th Annual Meeting of the Belgian Statistical Society (BSS - 2010).
Vancouver
1.
Loeys T, Rosseel Y, Baten K. A joint modeling approach for reaction time and accuracy in psycholinguistic experiments. 18th annual meeting of the Belgian statistical society, Abstracts. 2010.
MLA
Loeys, Tom, Yves Rosseel, and Kristof Baten. “A Joint Modeling Approach for Reaction Time and Accuracy in Psycholinguistic Experiments.” 18th Annual Meeting of the Belgian Statistical Society, Abstracts. 2010. Print.