Bayesian Rating using Glenn–David Paired Comparison Model with Non–Informative and Informative Priors

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ID: 316141
2025
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Abstract
In the technique of paired comparisons, objects are ranked since individual judgment. We use it when quantifiable measurement is not viable or impractical. In this study, the Glenn-David PC model under Bayesian framework is used to establish the rating of five brands of cold drinks. Bayesian analysis has been made using non-informative and informative priors. The posterior means are considered for the preference behavior of the cold drink brands. The predictive probabilities for a single future paired comparison of cold drink brands are also found. The posterior probabilities of the hypotheses for comparison of parameters for any two cold drink brands are obtained. Also, the preference probabilities for paired comparison are determined. The results obtained through Uniform and Normal-Gamma priors are compared. It is observed that similar results and same rankings for the cold drinks brands are achieved. The appropriateness of the model is tested by chi-squared statistic. All computations are made in SAS package by designing the programs/codes.
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imported_1780933764_6a26e48484ffe Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Qamar Rehman Abbasi, Zahid Iqbal
Journal Journal of Statistics
Year 2025
DOI
10.58575/r341cb27
URL
https://jstat.gcu.edu.pk/index.php/jstat/article/view/246
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