DocumentCode
2451472
Title
Using Bayesian Dominance Hierarchies to Determine Predictor Importance in Service Research Predictive Studies
Author
Xiaoyin Wang ; Duverger, P. ; Bansal, H.S.
Author_Institution
Coll. of Sci. & Math, Towson Univ., Towson, MD, USA
fYear
2012
fDate
24-26 May 2012
Firstpage
40
Lastpage
45
Abstract
Empirical results in business research derived from multiple linear regression models are often susceptible to issues of dimensionality and multicollinearity. We extend the current research practices for addressing multicollinearity by introducing an original method, Bayesian Dominance Hierarchy (BDH) to determine the relative importance of predictors in a multiple regression context.
Keywords
Bayes methods; commerce; regression analysis; BDH; Bayesian dominance hierarchies; business research; linear regression; predictor importance; service research predictive studies; Analytical models; Bayesian methods; Biological system modeling; Business; Context; Educational institutions; Predictive models; Bayesian; Dominance Analysis; Marketing Research Model; Predictor Importance;
fLanguage
English
Publisher
ieee
Conference_Titel
Service Sciences (IJCSS), 2012 International Joint Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4673-1992-8
Type
conf
DOI
10.1109/IJCSS.2012.68
Filename
6227792
Link To Document