Assessment and Validation in Quantile Composite-Based Path Modeling

The paper aims to introduce assessment and validation measures in Quantile Composite-based Path modeling. A quantile approach in the Partial Least Squares path modeling framework overcomes the classical exploration of average effects and highlights how and if the relationships among observed and unobserved variables change according to the explored quantile of interest. A final evaluation of the quality of the obtained results both from a descriptive (assessment) and inferential (validation) point of view is needed. The functioning of the proposed method is shown through a real data application in the area of the American Customer Satisfaction Index.

[1]  R. Koenker,et al.  Goodness of Fit and Related Inference Processes for Quantile Regression , 1999 .

[2]  Linglong Kong,et al.  Model-Robust Designs for Quantile Regression , 2014, 1403.1638.

[3]  Marko Sarstedt,et al.  Goodness-of-fit indices for partial least squares path modeling , 2013, Comput. Stat..

[4]  Giorgio Russolillo,et al.  Partial least squares algorithms and methods , 2013 .

[5]  V. E. Vinzi,et al.  REBUS-PLS: A response-based procedure for detecting unit segments in PLS path modelling , 2008 .

[6]  Kerstin Liehr-Gobbers,et al.  Chapter 29 Evaluation of Structural Equation Models Using the Partial Least Squares (PLS) Approach , 2010 .

[7]  Z. Ying,et al.  A resampling method based on pivotal estimating functions , 1994 .

[8]  Wynne W. Chin,et al.  Handbook of Partial Least Squares , 2010 .

[9]  Rudolf R. Sinkovics,et al.  The Use of Partial Least Squares Path Modeling in International Marketing , 2009 .

[10]  Cristina Davino,et al.  Quantile Regression: Theory and Applications , 2013 .

[11]  S. T. Buckland,et al.  An Introduction to the Bootstrap. , 1994 .

[12]  R. Koenker,et al.  Robust Tests for Heteroscedasticity Based on Regression Quantiles , 1982 .

[13]  C. Davino.  Combining PLS path modeling and quantile regression for the evaluation of customersatisfaction , 2014 .

[14]  M. Stone.  Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .

[15]  David F. Larcker,et al.  Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics: , 1981 .

[16]  Xuming He,et al.  Practical Confidence Intervals for Regression Quantiles , 2005 .

[17]  C. Fornell,et al.  Foundations of the American Customer Satisfaction Index , 2000 .

[18]  R. Koenker.  Quantile Regression: Name Index , 2005 .

[19]  Michel Tenenhaus,et al.  PLS path modeling , 2005, Comput. Stat. Data Anal..

[20]  Yang Li,et al.  Quantile Correlations and Quantile Autoregressive Modeling , 2012, 1209.6487.