An application of two sided power distribution in Bayesian analysis of paired comparison of relative importance of predictors in linear regression models

  • Authors

    • Xiaoyin Wang Towson University
    2015-08-07
    https://doi.org/10.14419/ijasp.v3i2.4573
  • Bayesian Estimate, Markov Chain Monte Carlo Method (MCMC), Paired Comparison, Relative Importance of Predictor, Two Sided Power Distribution

  • The purpose of determining the relative importance of predictors is to expose the extent of the individual contribution of a predictor in the presence of other predictors within a selected model. The goal of this article is to expand the current research practice by developing a statistical paired comparison model with Two Sided Power (TSP) link function in the Bayesian framework to evaluate the relative importance of each predictor in a multiple regression model. Results from simulation studies and empirical example reveal that the proposed Two Sided Power link function provides similar conclusions as the commonly used logit link function, but has more advantages from both practical and computational perspectives.

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