Articlei-Perception
Analyzing Response Times and Other Types of Time-to-Event Data Using Event History Analysis: A Tool for Mental Chronometry and Cognitive Psychophysiology.
Article in i-Perception. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Distinguishing between the exponential and Lindley distributions: An illustration from biological psychology.Behavior research methods · 2026Article
- Unconscious cognition without post hoc selection artifacts: From selective analysis to functional dissociations.Behavior research methods · 2026Article
- Training can enhance unconscious response priming on fast trials even when measuring consciousness on a trial-by-trial basis.Neuroscience of consciousness · 2025Article
- On the nonlinearity of the foreperiod effect.Scientific reports · 2024Article
- Self-control enhances vigilance performance in temporally irregular tasks: an fNIRS frontoparietal investigation.Frontiers in neuroergonomics · 2024Article
- Moving beyond response times with accessible measures of manual dynamics.Scientific reports · 2022Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this Methods article, we discuss and illustrate a unifying, principled way to analyze response time data from psychological experiments-and all other types of time-to-event data. We advocate the general application of discrete-time event history analysis (EHA) which is a well-established, intuitive longitudinal approach to statistically describe and model the shape of time-to-event distributions. After discussing the theoretical background behind the so-called hazard function of event occurrence in both continuous and discrete time units, we illustrate how to calculate and interpret the descriptive statistics provided by discrete-time EHA using two example data sets (masked priming, visual search). In case of discrimination data, the hazard analysis of response occurrence can be extended with a microlevel speed-accuracy trade-off analysis. We then discuss different approaches for obtaining inferential statistics. We consider the advantages and disadvantages of a principled use of discrete-time EHA for time-to-event data compared to (a) comparing means with analysis of variance, (b) other distributional methods available in the literature such as delta plots and continuous-time EHA methods, and (c) only fitting parametric distributions or computational models to empirical data. We conclude that statistically controlling for the passage of time during data analysis is
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.