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Communications in Statistics - Simulation and Computation Volume 51, 2022 - Issue 6
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Original Articles

Masking data: a solution to social desirability bias in paired comparison experiments

Said Farooq Shaha Department of Statistics, Quaid-i-Azam University, Islamabad, PakistanCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-1381-2775
ORCID Icon,
Salman Arif Cheemab School of Mathematical and Physical Sciences, University of Newcastle, Callaghan, NSW, Australia
,
Zawar Hussainc Department of Social and Allied Sciences, Cholistan University of Veterinary and Animal Sciences, Bahawalpur, PakistanORCID Iconhttps://orcid.org/0000-0002-5109-3652
ORCID Icon &
Ejaz Ali Shahd Department of Mathematics and Statistics, Hazara University, Mansehra, Pakistan
Pages 3149-3167 | Received 11 Mar 2019, Accepted 24 Dec 2019, Published online: 12 Jan 2020
 
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Abstract

This paper deals with the reduction of evasive answering bias in paired comparisons studies by providing a masking mechanism to the judges. Specifically, the Warner (Citation1965) masking design is applied in the application of Bradley and Terry (Citation1952) paired comparison model. For estimating the worth parameters and preference probabilities, Bayesian method of estimation is applied. To study the behavior of Bayes estimates and the effect of masking parameter, simulation study is performed. It is observed that the preference ordering is not disturbed when the number of judges is moderate to large. Also, the preference ordering is observed to be robust with respect to the extent of masking, when the number of judges is large. These findings are also supported by a numerical study using real data.

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