An Empirical Comparison of the Efficacy of Covariance-Based and Variance-Based SEM

51 Pages Posted: 28 Aug 2009

See all articles by Werner J. Reinartz

Werner J. Reinartz

University of Cologne; University of Cologne

Michael Haenlein

affiliation not provided to SSRN

Jörg Henseler

Institute for Management Research, Radboud University Nijmegen; Instituto Superior de Estatística e Gestão de Informação, Universidade Nova de Lisboa

Date Written: August, 27 2009

Abstract

Variance-based SEM, also known under the term partial least squares (PLS) analysis, is an approach that has gained increasing interest among marketing researchers in recent years. During the last 25 years, more than 30 articles have been published in leading marketing journals that have applied this approach instead of the more traditional alternative of covariance-based SEM (CBSEM). However, although an analysis of these previous publications shows that there seems to be at least an implicit agreement about the factors that should drive the choice between PLS analysis and CBSEM, no research has until now empirically compared the performance of these approaches given a set of different conditions. Our study addresses this open question by conducting a large-scale Monte-Carlo simulation. We show that justifying the choice of PLS due to a lack of assumptions regarding indicator distribution and measurement scale is often inappropriate, as CBSEM proves extremely robust with respect to violations of its underlying distributional assumptions. Additionally, CBSEM clearly outperforms PLS in terms of parameter consistency and is preferable in terms of parameter accuracy as long as the sample size exceeds a certain threshold (250 observations). Nevertheless, PLS analysis should be preferred when the emphasis is on prediction and theory development, as the statistical power of PLS is always larger than or equal to that of CBSEM; already, 100 observations can be sufficient to achieve acceptable levels of statistical power given a certain quality of the measurement model.

Keywords: Structural Equation Modeling, Maximum-likelihood, LISREL, Monte-Carlo Simulation

Suggested Citation

Reinartz, Werner J. and Reinartz, Werner J. and Haenlein, Michael and Henseler, Jörg, An Empirical Comparison of the Efficacy of Covariance-Based and Variance-Based SEM (August, 27 2009). INSEAD Working Paper No. 2009/44/MKT, Available at SSRN: https://ssrn.com/abstract=1462666 or http://dx.doi.org/10.2139/ssrn.1462666

Werner J. Reinartz (Contact Author)

University of Cologne ( email )

Albertus-Magnus-Platz
Cologne, 50923
Germany

University of Cologne ( email )

Albertus-Magnus-Platz
Cologne, 50923
Germany

Michael Haenlein

affiliation not provided to SSRN

Jörg Henseler

Institute for Management Research, Radboud University Nijmegen ( email )

Thomas van Aquinostraat 3
P.O. Box 9108
Nijmegen, 6500HK
Netherlands
+31 24 3611854 (Phone)
+31 24 3611933 (Fax)

HOME PAGE: http://www.ru.nl/fm/henseler

Instituto Superior de Estatística e Gestão de Informação, Universidade Nova de Lisboa ( email )

Campus de Campolide
Lisbon, 1070-312
Portugal

HOME PAGE: http://www.henseler.com