Prediction Oriented Classification in PLS Path Modeling

Structural Equation Modelling methods traditionally assume the homogeneity of all the units on which a model is estimated. In many cases, however, this assumption may turn to be false; the presence of latent classes not accounted for by the global model may lead to biased or erroneous results in terms of model parameters and model quality. The traditional multi-group approach to classification is often unsatisfying for several reasons; above all because it leads to classes homogeneous only with respect to external criteria and not to the theoretical model itself.

[1]  Kamel Jedidi,et al.  STEMM: A General Finite Mixture Structural Equation Model , 1997 .

[2]  R. Bagozzi.  Principles of marketing research , 1994 .

[3]  F. Bookstein,et al.  Neurobehavioral effects of prenatal alcohol: Part II. Partial least squares analysis. , 1989, Neurotoxicology and teratology.

[4]  A. Goldberger,et al.  Structural Equation Models in the Social Sciences. , 1974 .

[5]  Christian Charles,et al.  Régression typologique et reconnaissance des formes , 1977 .

[6]  K. Jöreskog.  A general method for analysis of covariance structures , 1970 .

[7]  W. DeSarbo,et al.  A maximum likelihood methodology for clusterwise linear regression , 1988 .

[8]  K. Jöreskog.  A General Method for Estimating a Linear Structural Equation System. , 1970 .

[9]  S. Wold,et al.  The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses , 1984 .

[10]  D. Sörbom.  A GENERAL METHOD FOR STUDYING DIFFERENCES IN FACTOR MEANS AND FACTOR STRUCTURE BETWEEN GROUPS , 1974 .

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

[12]  Gilbert Saporta,et al.  Clusterwise PLS regression on a stochastic process , 2002, Comput. Stat. Data Anal..

[13]  Frank Huber,et al.  Capturing Customer Heterogeneity using a Finite Mixture PLS Approach , 2002 .

[14]  S. Wold,et al.  Multivariate Data Analysis in Chemistry , 1984 .

[15]  K. Jöreskog.  Simultaneous factor analysis in several populations , 1971 .

[16]  Dag Sörbom,et al.  DETECTION OF CORRELATED ERRORS IN LONGITUDINAL DATA , 1975 .

[17]  Lutz Hildebrandt,et al.  Analyzing Multigroup Data with Structural Equation Models , 2000 .

[18]  M. Wedel,et al.  Market Segmentation: Conceptual and Methodological Foundations , 1997 .

[19]  W. DeSarbo,et al.  An Empirical Pooling Approach for Estimating Marketing Mix Elasticities with PIMS Data , 1993 .

[20]  Helmuth Späth,et al.  Algorithm 39 Clusterwise linear regression , 1979, Computing.

[21]  Geoffrey J. McLachlan,et al.  FITTING FINITE MIXTURE MODELS IN A REGRESSION CONTEXT , 1992 .

[22]  H. Wold.  Soft Modelling by Latent Variables: The Non-Linear Iterative Partial Least Squares (NIPALS) Approach , 1975, Journal of Applied Probability.

[23]  Svante Wold,et al.  PLS DISCRIMINANT PLOTS , 1986 .