DocumentCode
729946
Title
Performance simulation of unforced choice paradigms in parametric psychometric procedures
Author
Hatzfeld, Christian ; Kupnik, Mario ; Werthschutzky, Roland
Author_Institution
Inst. of Electromech. Design, Tech. Univ. Darmstadt, Darmstadt, Germany
fYear
2015
fDate
22-26 June 2015
Firstpage
475
Lastpage
481
Abstract
This paper shows an implementation of the Ψ and UML (Updated Maximum Likelihood) methods to incorporate unforced choice paradigms (nAUC) and simulation results for repeatability, efficiency and accuracy. Parametric methods like Ψ and UML promise higher accuracy and efficiency compared to classic and non-parametric methods and support fixed sets of stimuli. Unforced choice paradigms have shown similar performance as forced choice paradigms but are expected to create less confusion for test subjects for low stimuli intensities.
Keywords
maximum likelihood estimation; psychometric testing; Updated Maximum Likelihood methods; nonparametric methods; parametric psychometric procedures; unforced choice paradigms; Accuracy; Convergence; Entropy; Haptic interfaces; Maximum likelihood estimation; Unified modeling language;
fLanguage
English
Publisher
ieee
Conference_Titel
World Haptics Conference (WHC), 2015 IEEE
Conference_Location
Evanston, IL
Type
conf
DOI
10.1109/WHC.2015.7177757
Filename
7177757
Link To Document