Paired Comparison Modeling with Bayesian Analysis: Statistics for Social Sciences

The method of paired comparisons is a technique in which the treatments or stimuli are presented in pairs to some respondents, who depending upon sensory evaluation, pick the better one. The experiment is repeatedly executed for all the treatments with a number of respondents to reach certain ranking of the treatments. In this study, an attempt is made to develop paired comparison models, namely the Pareto model and the Cauchy model. The Cauchy model is also extended to accommodate ties. Bayesian analysis is a modern inferential technique which endeavors to estimate parameters of an underlying posterior distribution based on a prior and an observed distribution. The developed models, along with the Stern (1990a) Chi-square model, are analyzed in Bayesian framework. As an illustration, we use a real data set for the years 2000-2006 to rank five top-ranked one-day-international cricket teams. The analysis comprises finding the posterior means, joint posterior modes, marginal posterior distributions, preference probabilities, predictive probabilities and posterior probabilities of hypotheses. The plausibility of the models is also tested.