Analyzing reaction times
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Keywords

Reaction times
distributions
outliers
transformations
temporal dependencies
linear mixed-effects modeling

How to Cite

Harald Baayen, R., & Milin, P. (2010). Analyzing reaction times. International Journal of Psychological Research, 3(2), 12–28. https://doi.org/10.21500/20112084.807

Abstract

Reaction times (RTs) are an important source of information in experimental psychology. Classical methodological considerations pertaining to the statistical analysis of RT data are optimized for analyses of aggregated data, based on subject or item means (c.f., Forster & Dickinson, 1976). Mixed-effects modeling (see, e.g., Baayen, Davidson, & Bates, 2008) does not require prior aggregation and allows the researcher the more ambitious goal of predicting individual responses. Mixed-modeling calls for a reconsideration of the classical methodological strategies for analysing rts. In this study, we argue for empirical exibility with respect to the choice of transformation for the RTs. We advocate minimal a-priori data trimming, combined with model criticism. We also show how trial-to-trial, longitudinal dependencies between individual observations can be brought into the statistical model. These strategies are illustrated for a large dataset with a non-trivial random-effects structure. Special attention is paid to the evaluation of interactions involving fixed-effect factors that partition the levels sampled by random-effect factors.
https://doi.org/10.21500/20112084.807
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References

Baayen, R. H. (2007). Storage and computation in the mental lexicon. In G. Jarema & G. Libben (Eds.), The mental lexicon: Core perspectives. Oxford: Elsevier.

Baayen, R. H. (2010). languager: Data sets and functions with "analyzing linguistic data: A practical introduction to statistics". [Computer software manual]. Available from http://CRAN.R-project.org/package=languageR (R package version 1.0)

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