New paper on PLS-SEM

19.04.2016 -  

The paper “Segmentation of PLS Path Models by Iterative Reweighted Regressions” authored by Rainer Schlittgen (University of Hamburg), Christian M. Ringle (Hamburg University of Technology), Marko Sarstedt (OvGU), and Jan-Michael Becker (University of Cologne) has been accepted for publication in Journal of Business Research. In their paper, the authors introduce a new approach for uncovering and treating unobserved heterogeneity in partial least squares structural equation modeling (PLS). The iterative reweighted regressions segmentation method for PLS (PLS-IRRS) effectively identifies and treats unobserved heterogeneity in data sets. Compared to existing alternatives, PLS-IRRS is multiple times faster while delivering results of the same quality. Researchers should therefore routinely use PLS-IRRS to address the critical issue of unobserved heterogeneity in PLS.

Letzte Änderung: 28.04.2016 - Ansprechpartner: Webmaster