Article2019

Factors versus Composites: Guidelines for Choosing the Right Structural Equation Modeling Method

410 citations0/0 files storedProject Management Journal

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Psychometric Methodologies and Testing Construction Project Management and Performance Business Strategies and Management Research

Abstract

Structural equation modeling (SEM) is a widely applied and useful tool for project management scholars. In this Thoughtlet article, we critically reflect on the measurement philosophy underlying the two streams of SEM and their adequacy for estimating relationships among concepts commonly encountered in the field (e.g., team performance). We also discuss considerations to ponder when making the choice between the two types of SEM as well as between SEM and regression analysis.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 410 citations exist upstream.

References

2018When to use and how to report the results of PLS-SEM 2019Predictive model assessment in PLS-SEM: guidelines for using PLSpredict 2016Testing measurement invariance of composites using partial least squares 2017Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods 2016Estimation issues with PLS and CBSEM: Where the bias lies!2019Rethinking some of the rethinking of partial least squares 2018Addressing Endogeneity in International Marketing Applications of Partial Least Squares Structural Equation Modeling 2002Latent Variables in Psychology and the Social Sciences

Cited by

2020Fake news and COVID-19: modelling the predictors of fake news sharing among social media users 2022Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendations 2020Cutoff criteria for overall model fit indexes in generalized structured component analysis 2021PLS‐SEM : Prediction‐oriented solutions for HRD researchers 2024Going beyond the untold facts in PLS–SEM and moving forward

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.