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RandseqR: An R Package for Describing Performance on the Random Number Generation Task.

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|May 21, 2021
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The Random Number Generation (RNG) task, a neuropsychological tool for executive functioning, can now be analyzed using dynamic, non-linear methods. The new RandseqR R-package offers advanced analysis for current scientific and clinical use.

Keywords:
R-packageassessmentcontextual neuropsychologyexecutive functionrandom number generationrecurrence qualification analysis

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Area of Science:

  • Neuropsychology
  • Cognitive Psychology
  • Data Science

Background:

  • The Random Number Generation (RNG) task is a long-standing neuropsychological assessment for executive functioning.
  • Current understanding views executive behavior as a dynamic process, necessitating updated analytical methods for tasks like RNG.
  • Traditional analysis of RNG data may not capture the complex dynamics of behavior.

Purpose of the Study:

  • To introduce RandseqR, an R-package designed for processing random number sequences generated in the RNG task.
  • To enable the application of non-linear methods, specifically Recurrence Quantification Analysis (RQA), to RNG data.
  • To update the RNG task for contemporary scientific and clinical applications by integrating dynamic analysis.

Main Methods:

  • Development of RandseqR, an R-package integrating classic randomization measures and RQA.
  • Application of non-linear time series analysis techniques to random number sequences.
  • Comparative analysis of traditional versus dynamic (RQA) measures for RNG data.

Main Results:

  • RandseqR provides a flexible, fast, and user-friendly platform for analyzing RNG sequences.
  • The package successfully combines traditional randomization metrics with advanced RQA.
  • RandseqR facilitates the interpretation of RNG task results within a dynamic framework of executive functioning.

Conclusions:

  • The RandseqR package modernizes the RNG task by incorporating dynamic and non-linear analytical approaches.
  • This R-package enhances the utility of the RNG task for both research and clinical practice in neuropsychology.
  • RandseqR supports a more nuanced understanding of executive functioning through dynamic behavioral analysis.