Assessing and testing the goodness-of-fit of PLS path models

Research output: Contribution to conferencePaper

Abstract

This paper introduces a family of goodness-of-fit measures for partial least squares path modeling (PLS). It shows that PLS estimates the parameters of a composite factor model. The discrepancy between the empirical covariance matrix and the covariance matrix implied by the composite factor model permits quantifying the model fit. The paper proposes statistical inference based on the bootstrap as an exact test of model fit. Moreover, it suggests the standardized root mean square residual as an approximate measure of model fit. These two goodness-of-fit measures enable analysts to empirically assess the validity of interrelated composites of observed variables, i.e., conduct a confirmatory composite analysis by means of PLS. Finally, the paper provides recommendations for conducting and reporting typical PLS analyses.
Original languageEnglish
Publication statusPublished - 9 May 2014
EventThe 3rd Annual Conference of the Dutch/Flemish Classification Society (Vereniging voor Ordinatie en Classificatie - VOC) - Leiden, Netherlands
Duration: 9 May 20149 May 2014
Conference number: 3

Conference

ConferenceThe 3rd Annual Conference of the Dutch/Flemish Classification Society (Vereniging voor Ordinatie en Classificatie - VOC)
Abbreviated title3rd VOC Conference
CountryNetherlands
CityLeiden
Period9/05/149/05/14

Fingerprint Dive into the research topics of 'Assessing and testing the goodness-of-fit of PLS path models'. Together they form a unique fingerprint.

  • Cite this

    Henseler, J. (2014). Assessing and testing the goodness-of-fit of PLS path models. Paper presented at The 3rd Annual Conference of the Dutch/Flemish Classification Society (Vereniging voor Ordinatie en Classificatie - VOC), Leiden, Netherlands.