Abstract
The PLS approach is a widely used technique to estimate path models relating various blocks of variables measured from the same population. It is frequently applied in the social sciences and in economics. In this type of applications, deviations from normality and outliers may occur, leading to an efficiency loss or even biased results. In the current paper, a robust path model estimation technique is being proposed, the partial robust M (PRM) approach. In an example its benefits are illustrated.
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Serneels, S., Croux, C., Filzmoser, P., Van Espen, P.J. (2006). The Partial Robust M-approach. In: Spiliopoulou, M., Kruse, R., Borgelt, C., Nürnberger, A., Gaul, W. (eds) From Data and Information Analysis to Knowledge Engineering. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31314-1_27
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DOI: https://doi.org/10.1007/3-540-31314-1_27
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