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Theoretical Versus Mathematical Approach to Modeling Psychological and Physiological Data

  • Lauren Reinerman-JonesEmail author
  • Stephanie J. Lackey
  • Julian AbichIV
  • Brandon Sollins
  • Irwin Hudson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9743)

Abstract

Variable selection for predictive modeling has traditionally relied on theory in the psychological domain. Given the recent advancements in computing technology and availability, researchers are able to utilize more sophisticated mathematical modeling techniques with greater ease. The challenge becomes evaluating whether theory or mathematics should be relied upon for model development. The presented analyses compared the use of hierarchical and stepwise variable selection methods during a predictive modeling task using linear regression. The results show that the stepwise variable selection method is able to obtain a more efficient model than the hierarchical variable selection method. Implications and recommendations for researchers are further discussed.

Keywords

Cognitive modeling Perception Emotion Interaction Electroencephalography Brain activity measurement Physiological measuring Human performance 

Notes

Acknowledgements

This work was in part supported by the US Army Research Laboratory (ARL) (W91CRB-08-D-0015). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of ARL or the US Government.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Lauren Reinerman-Jones
    • 1
    Email author
  • Stephanie J. Lackey
    • 2
  • Julian AbichIV
    • 1
  • Brandon Sollins
    • 1
  • Irwin Hudson
    • 3
  1. 1.Institute for Simulation and Training (IST)University of Central Florida (UCF)OrlandoUSA
  2. 2.Design InteractiveOrlandoUSA
  3. 3.U.S. Army Research LaboratoryOrlandoUSA

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