Measurement invariance testing in partial least squares structural equation modeling

TY - JOUR

T1 - Measurement invariance testing in partial least squares structural equation modeling

AU - Liengaard, Benjamin Dybro

PY - 2024/4

Y1 - 2024/4

N2 - When using structural equation modeling, comparison across time or groups can be misleading if measures are not invariant. Partial least squares structural equation modeling (PLS-SEM) is a method widely used in business research, but its ability to test for measurement invariance is limited. This study introduces a comprehensive approach for measurement invariance testing in reflective measurement models in PLS-SEM. The methodology diverges from the traditional measurement invariance of composite models (MICOM) approach and expands the possibilities of measurement invariance testing in three areas: 1) providing statistical tests to validate the comparison of latent means across groups; 2) measurement invariance testing in longitudinal studies; and 3) the ability to simultaneously assess measurement invariance across multiple groups. Additionally, this study proposes a strategy to address measurement invariance rejections in large-sample studies. The paper offers guidelines for the MI tests, and an empirical example illustrates their utility in facilitating experimental approaches in PLS-SEM.

AB - When using structural equation modeling, comparison across time or groups can be misleading if measures are not invariant. Partial least squares structural equation modeling (PLS-SEM) is a method widely used in business research, but its ability to test for measurement invariance is limited. This study introduces a comprehensive approach for measurement invariance testing in reflective measurement models in PLS-SEM. The methodology diverges from the traditional measurement invariance of composite models (MICOM) approach and expands the possibilities of measurement invariance testing in three areas: 1) providing statistical tests to validate the comparison of latent means across groups; 2) measurement invariance testing in longitudinal studies; and 3) the ability to simultaneously assess measurement invariance across multiple groups. Additionally, this study proposes a strategy to address measurement invariance rejections in large-sample studies. The paper offers guidelines for the MI tests, and an empirical example illustrates their utility in facilitating experimental approaches in PLS-SEM.

KW - Longitudinal

KW - Measurement

KW - Measurement invariance

KW - Multigroup analysis

KW - Partial least squares

KW - structural equation modeling

KW - Structural equation modeling

UR - http://www.scopus.com/inward/record.url?scp=85188678013&partnerID=8YFLogxK

U2 - 10.1016/j.jbusres.2024.114581

DO - 10.1016/j.jbusres.2024.114581

M3 - Journal article

SN - 0148-2963

VL - 177

JO - Journal of Business Research

JF - Journal of Business Research

M1 - 114581

ER -