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Area of Science:

  • Cognitive Psychology
  • Computational Linguistics
  • Psycholinguistics

Background:

  • Response times (RTs) and their distributions offer insights into cognitive processes.
  • Understanding how word properties like frequency and length affect RT distributions is crucial for cognitive theories.
  • Existing methods may not fully capture the complex relationship between word characteristics and RT variability.

Purpose of the Study:

  • To introduce a novel statistical methodology, stratified distributional analysis (SDA), for quantitatively assessing determinants of response time distributions.
  • To investigate the influence of word frequency and length on response time distributions using large-scale lexical decision data.
  • To determine the best probability distribution and word occurrence measure for modeling response time distributions.

Main Methods:

  • Applied stratified distributional analysis (SDA) to millions of lexical decision response times from the English and British Lexicon Projects.
  • Analyzed response time distributions as a function of word frequency and word length.
  • Compared lognormal, Wald, and gamma distributions, and evaluated word form frequencies, discourse contextual diversity, and user contextual diversity.

Main Results:

  • Response time distributions were best described by a lognormal distribution when word occurrence was quantified using contextual diversity measures.
  • SDA, utilizing a hierarchical Bayesian framework, provided participant-level posterior distributions for distributional parameters.
  • The methodology enabled probabilistic predictions of response times based on word frequency and length.

Conclusions:

  • Stratified distributional analysis (SDA) effectively elucidates the mechanisms governing response time generation by fitting probability distributions.
  • The findings highlight the utility of contextual diversity measures in modeling word processing.
  • SDA is a versatile tool applicable to various cognitive tasks beyond lexical decision, including word-naming and eye-tracking.