On Optimal Allocation of Treatment/Condition Variance in Principal Component Analysis


  •  André Beauducel    
  •  Norbert Hilger    

Abstract

The allocation of a (treatment) condition-effect on the wrong principal component (misallocation of variance) in principal component analysis (PCA) has been addressed in research on event-related potentials of the electroencephalogram. However, the correct allocation of condition-effects on PCA components might be relevant in several domains of research. The present paper investigates whether different loading patterns at each condition-level are a basis for an optimal allocation of between-condition variance on principal components. It turns out that a similar loading shape at each condition-level is a necessary condition for an optimal allocation of between-condition variance, whereas a similar loading magnitude is not necessary.



This work is licensed under a Creative Commons Attribution 4.0 License.
  • Issn(Print): 1927-7032
  • Issn(Onlne): 1927-7040
  • Started: 2012
  • Frequency: bimonthly

Journal Metrics

Google-based Impact Factor (2018): 2.7

  • h-index (August 2018): 11
  • i10-index (August 2018): 15
  • h5-index (August 2018): 9
  • h5-median(August 2018): 16

( The data was calculated based on Google Scholar Citations. Click Here to Learn More. )

Contact