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Systems factorial technology (SFT) offers nonparametric models and the double factorial paradigm (DFP) to analyze cognitive information processing. This study provides a tutorial and R package for applying these powerful methods in psychological research.

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Area of Science:

  • Cognitive Psychology
  • Mathematical Psychology
  • Psychometrics

Background:

  • Systems factorial technology (SFT) provides nonparametric models and measures for cognitive information processing.
  • The double factorial paradigm (DFP) is a theory-driven experimental methodology within SFT.
  • Assessing cognitive mechanisms for processing multiple information sources is crucial in various psychological tasks.

Purpose of the Study:

  • To provide an overview of SFT's model-based measures.
  • To offer a tutorial on designing DFP experiments for comprehensive SFT analysis.
  • To introduce and demonstrate a new R package for SFT analysis.

Main Methods:

  • Overview of Systems factorial technology (SFT) nonparametric models and measures.
  • Description of the double factorial paradigm (DFP) experimental design.
  • Demonstration of a new R package for statistical computing in SFT analyses.

Main Results:

  • Illustrative examples showcase the broad applicability of SFT and DFP across psychology.
  • The R package facilitates the implementation of SFT analyses.
  • The study provides a practical guide for researchers interested in cognitive processing.

Conclusions:

  • SFT and DFP offer a robust framework for understanding cognitive information processing.
  • The developed R package enhances the accessibility and application of SFT methods.
  • This work supports the advancement of quantitative psychology and cognitive modeling.