Paper
18 December 2003 Louis Leon Thurstone in Monte Carlo: creating error bars for the method of paired comparison
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Proceedings Volume 5294, Image Quality and System Performance; (2003) https://doi.org/10.1117/12.526215
Event: Electronic Imaging 2004, 2004, San Jose, California, United States
Abstract
The method of paired comparison is often used in experiments where perceptual scale values for a collection of stimuli are desired, such as in experiments analyzing image quality. Thurstone's Case V of his Law of Comparative Judgments is often used as the basis for analyzing data produced in paired comparison experiments. However, methods for determining confidence intervals and critical distances for significant differences based on Thurstone's Law have been elusive leading some to abandon the simple analysis provided by Thurstone's formulation. In order to provide insight into this problem of determining error, Monte Carlo simulations of paired comparison experiments were performed based on the assumptions of uniformly normal, independent, and uncorrelated responses from stimulus pair presentations. The results from these multiple simulations show that the variation in the distribution of experimental results of paired comparison experiments can be well predicted as a function of stimulus number and the number of observations. Using these results, confidence intervals and critical values for comparisons can be made using traditional statistical methods. In addition the results from simulations can be used to analyze goodness-of-fit techniques.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ethan D. Montag "Louis Leon Thurstone in Monte Carlo: creating error bars for the method of paired comparison", Proc. SPIE 5294, Image Quality and System Performance, (18 December 2003); https://doi.org/10.1117/12.526215
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Cited by 15 scholarly publications.
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KEYWORDS
Monte Carlo methods

Statistical analysis

Error analysis

Image quality

Computer simulations

Analytical research

Data corrections

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