Treating unobserved heterogeneity in PLS path modeling: a comparison of FIMIX-PLS with different data analysis strategies
Abstract
In the social science disciplines, the assumption that the data stem from a single homogeneous population is often unrealistic in respect of empirical research. When applying a causal modeling approach, such as partial least squares path modeling, segmentation is a key issue in coping with the problem of heterogeneity in the estimated cause–effect relationships. This article uses the novel finite-mixture partial least squares (FIMIX-PLS) method...
Paper Details
Title
Treating unobserved heterogeneity in PLS path modeling: a comparison of FIMIX-PLS with different data analysis strategies
Published Date
Aug 1, 2010
Volume
37
Issue
8
Pages
1299 - 1318
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