A hierarchical approach for fitting curves to response time measurements |
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Authors: | Jeffrey N Rouder Francis Tuerlinckx Paul Speckman Jun Lu Pablo Gomez |
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Institution: | (1) University of Leuven, Leuven, Belgium;(2) American University, Washington, DC;(3) DePaul University, Chicago, Illinois;(4) Department of Psychological Sciences, University of Missouri, 210 McAlester Hall, 65211 Columbia, MO |
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Abstract: | Understanding how response time (RT) changes with manipulations has been critical in distinguishing among theories in cognition.
It is well known that aggregating data distorts functional relationships (e.g., Estes, 1956). Less well appreciated is a second
pitfall: Minimizing squared errors (i.e., OLS regression) also distorts estimated functional forms with RT data. We discuss
three properties of RT that should be modeled for accurate analysis and, on the basis of these three properties, provide a
hierarchical Weibull regression model for regressing RT onto covariates. Hierarchical regression model analysis of lexical
decision task data reveals that RT decreases as a power function of word frequency with the scale of RT decreasing 11% for
every doubling of word frequency. A detailed discussion of the model and analysis techniques are presented as archived materials
and may be downloaded from www.psychonomic.org/archive. |
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