Theoretical Versus Mathematical Approach To Modeling Psychological And Physiological Data

Keywords

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

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.

Publication Date

1-1-2016

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

9743

Number of Pages

383-393

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/978-3-319-39955-3_36

Socpus ID

84978821880 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84978821880

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