Discriminant validity assessment in PLS-SEM: A comprehensive composite-based approach

The article below puts forth a comprehensive composite-based perspective on how one can conduct discriminant validity assessment, in the context of structural equation modeling via partial least squares (PLS-SEM).

Rasoolimanesh, S. M. (2022). Discriminant validity assessment in PLS-SEM: A comprehensive composite-based approach. Data Analysis Perspectives Journal, 3(2), 1-8.

Link to full-text file for this and other DAPJ articles:

https://scriptwarp.com/dapj/#Published_Articles

Abstract:

This paper aims to discuss modern approaches to assess discriminant validity in the context of structural equation modeling via partial least squares (PLS-SEM). It illustrates the application of these approaches using the WarpPLS 7.0 software. The Fornell-Larcker criterion, crossloadings method, heterotrait-monotrait (HTMT) ratio, and full collinearity test have been discussed in this paper. A step-by-step guide is provided to assess discriminant validity using these four tests in WarpPLS 7.0. The first three criteria are applicable for reflective constructs, while the full collinearity test can be applied for both reflective and formative constructs. In different social science disciplines, a combination of reflective and formative constructs is a common practice, therefore reporting the full collinearity test for the assessment of discriminant validity can be an advantage.

Best regards to all!

Reliability assessment in SEM models with composites and factors: A modern perspective

The article below puts forth a modern perspective on how one can conduct reliability assessments in models with composites and factors, in the context of structural equation modeling via partial least squares (PLS-SEM).

Canatay, A., Emegwa, T., Lybolt, L. M. & Loch, K. D. (2022). Reliability assessment in SEM models with composites and factors: A modern perspective. Data Analysis Perspectives Journal, 3(1), 1-6.

Link to full-text file for this and other DAPJ articles:

https://scriptwarp.com/dapj/#Published_Articles

Abstract:

This paper’s focus is on reliability tests for both composite-based and factor-based analysis algorithms in structural equation modeling through partial least squares (PLS-SEM). We illustrate this analysis employing a widely used PLS-SEM software tool, WarpPLS. The results show the magnitude of differences between the two approaches, suggesting that the estimates of coefficients obtained using the factor-based approach are more conservative than those obtained using the corresponding composite-based approach.

Best regards to all!

Moderated mediation, segmentation delta method, J-curve emergence, and causality assessment: Article

The article below discusses moderated mediation and the related emergence of J-curve relationships, in a context that is relevant to researchers employing structural equation modeling via partial least squares (PLS-SEM).

The article lays out three steps to combine moderation and J-curve analyses, with the goal of more fully understanding the underlying moderated mediation relationships. It proposes a new segmentation delta method to test for J-curve emergence, as part of this framework.

Finally, the article discusses three causality assessment indices that are used to show that the model used in the article is generally sound in terms of causality.

Kock, N. (2021). Moderated mediation and J-curve emergence in path models: An information systems research perspective. Journal of Systems and Information Technology, 23(3), 303-321.

Link to full-text file for this article:

Click for PDF file

Abstract (structured):

Purpose. J-curve relationship analyses can provide valuable insights to information systems (IS) researchers. We discuss moderated mediation in IS research and the related emergence of J-curve relationships. Design/methodology/approach. Building on an illustrative study in the field of IS, we lay out three steps to combine moderation and J-curve analyses, with the goal of more fully understanding the underlying moderated mediation relationships. We propose a new segmentation delta method to test for J-curve emergence, as part of this framework. Findings. We show, in the context of this study, the complementarity of moderation and J-curve analyses. Research limitations/implications. Currently, IS researchers rarely conduct moderation and J-curve analyses in a complementary way, even though there are software tools, and related methods, which allow them to do so in a relatively straightforward way. Originality/value. Our analyses were conducted with the software WarpPLS, a widely used tool that allows for moderated mediation and J-curve analyses, in a way that is fully compatible with the set of steps presented in this paper.

Best regards to all!

PLS Applications Symposium; 6-8 April 2022; Laredo, Texas

PLS Applications Symposium; 6-8 April 2022; Laredo, Texas
(Abstract submissions accepted until 18 February 2022)

*** Attendance (face-to-face or online) ***

The Symposium will be conducted as part of the multidisciplinary Annual Western Hemispheric Trade Conference, organized by the Center for the Study of Western Hemispheric Trade. Our workshop in PLS-SEM will be conducted entirely online. Our expectation is that participants will be allowed to attend Conference sessions either face-to-face or online.

When indicating the type of their submission, participants should indicate whether they intend to attend face-to-face or online. This should be done within parentheses after indicating the submission type. For example - "Type of submission: Presentation (online)".

Due to the uncertainty of the COVID-19 pandemic, the Center reserves the right to transition to a fully virtual Conference to comply with guidelines from the CDC as well as state and local governments.

*** Only abstracts are needed for the submissions ***

The partial least squares (PLS) method has increasingly been used in a variety of fields of research and practice, particularly in the context of PLS-based structural equation modeling (SEM). The focus of this Symposium is on the application of PLS-based methods, from a multidisciplinary perspective. For types of submissions, deadlines, and other details, please visit the Symposium’s web site:

https://plsas.net

*** Workshop on PLS-SEM ***

On 6 April 2022 a full-day workshop on PLS-SEM will be conducted by Dr. Ned Kock and Dr. Geoffrey Hubona, using the software WarpPLS. Dr. Kock is the original developer of this software, which is one of the leading PLS-SEM tools today; used by thousands of researchers from a wide variety of disciplines, and from many different countries. Dr. Hubona has extensive experience conducting research and teaching topics related to PLS-SEM, using WarpPLS and a variety of other tools. This workshop will be hands-on and interactive, and will have two parts: (a) basic PLS-SEM issues, conducted in the morning (9 am - 12 noon) by Dr. Hubona; and (b) intermediate and advanced PLS-SEM issues, conducted in the afternoon (2 pm - 5 pm) by Dr. Kock. Participants may attend either one, or both of the two parts.

The following topics, among others, will be covered - Running a Full PLS-SEM Analysis - Conducting a Moderating Effects Analysis - Viewing Moderating Effects via 3D and 2D Graphs - Creating and Using Second Order Latent Variables - Viewing Indirect and Total Effects - Viewing Skewness and Kurtosis of Manifest and Latent Variables - Viewing Nonlinear Relationships - Solving Collinearity Problems - Conducting a Factor-Based PLS-SEM Analysis - Using Consistent PLS Factor-Based Algorithms - Exploring Statistical Power and Minimum Sample Sizes - Exploring Conditional Probabilistic Queries - Exploring Full Latent Growth - Conducting Multi-Group Analyses - Assessing Measurement Invariance - Creating Analytic Composites.

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Ned Kock
Symposium Chair
https://plsas.net

Robustness tests in PLS-SEM: Video for the Qatar Chapter of the Decision Sciences Institute

The so-called "robustness" tests that some refer to, in connection with PLS-SEM, are generally tests of: nonlinearity, common method bias, and endogeneity. In WarpPLS, nonlinearity can be tested via full latent growth, commom method bias via FCVIFs, and endogeneity via instrumental variables. The video linked below covers most of these issues.

https://youtu.be/I3YYdpdXhII

This video is of a presentation to faculty and students at the Qatar Chapter of the Decision Sciences Institute on the topics of factor-based PLS-SEM (PLSF-SEM), endogeneity, and common method bias. (SEM = structural equation modeling.) Addressing these issues helps with publishing in top-tier information systems and decision sciences journals, among others.

Best regards to all!

Common structural variation reduction in PLS-SEM: Replacement analytic composites and the one fourth rule

The article below explains how one can accomplish a common structural variation reduction, via replacement analytic composites and the one fourth rule, in the context of structural equation modeling via partial least squares (PLS-SEM).

Kock, N. (2021). Common structural variation reduction in PLS-SEM: Replacement analytic composites and the one fourth rule. Data Analysis Perspectives Journal, 2(5), 1-6.

Link to full-text file for this and other DAPJ articles:

https://scriptwarp.com/dapj/#Published_Articles

Abstract:

Path coefficients may be distorted, in the context of structural equation modeling via partial least squares (PLS-SEM), due to excess common structural variation shared in a model. This may be caused by methodological issues; e.g., the use of highly correlated but conceptually distinct latent variables, or common method bias. We discuss a common structural variation reduction procedure using WarpPLS, a leading PLS-SEM software tool. This procedure relies on the creation of analytic composites as replacements for latent variables, where the weights are one fourth of the original path coefficients among the latent variables and their predictors in the structural model, and with signs that are the opposites of the signs of the original path coefficients.

Best regards to all!

Testing a moderated mediation in PLS-SEM: A full latent growth approach

The article below explains how one can test moderated mediation effects in the context of structural equation modeling via partial least squares (PLS-SEM).

Hubona, G., & Belkhamza, Z. (2021). Testing a moderated mediation in PLS-SEM: A full latent growth approach. Data Analysis Perspectives Journal, 2(4), 1-5.

Link to full-text file for this and other DAPJ articles:

https://scriptwarp.com/dapj/#Published_Articles

Abstract:

There are various techniques for separately analyzing moderation and mediation effects in partial least squares structural equation models (PLS-SEM). These individual techniques are rather straightforward and widely understood. However, valid approaches for testing more complex moderated mediation effects that are embedded together in a single model are less well understood. In this paper, we explain and illustrate one approach to such an analysis using a complex model with numerous embedded moderated mediation relationships utilizing WarpPLS, a leading PLS-SEM software tool.

Enjoy!

Convergent validity assessment in PLS-SEM: A loadings-driven approach

The article below explains how one can conduct a convergent validity assessment in the context of structural equation modeling via partial least squares (PLS-SEM).

Amora, J. T. (2021). Convergent validity assessment in PLS-SEM: A loadings-driven approach. Data Analysis Perspectives Journal, 2(3), 1-6.

Link to PDF file for this and other DAPJ articles:

https://scriptwarp.com/dapj/#Published_Articles

Abstract:

Assessment of convergent validity of latent variables is one of the steps in conducting structural equation modeling via partial least squares (PLS-SEM). In this paper, we illustrate such an assessment using a loadings-driven approach. The analysis employs WarpPLS, a leading PLS-SEM software tool.

Enjoy!

A thank you note to the participants in the 2021 PLS Applications Symposium

This is just a thank you note to those who participated, either as presenters or members of the audience, in the 2021 PLS Applications Symposium:

https://plsas.net

As in previous years, it seems that it was a good idea to run the Symposium as part of the Western Hemispheric Trade Conference. This allowed attendees to take advantage of a subsidized registration fee, and also participate in other Conference sessions.

I have been told that the proceedings will be available soon, if they are not available yet, from the Western Hemispheric Trade Conference web site, which can be reached through the Symposium web site (link above).

Also, we had a nice full-day workshop on PLS-SEM using the software WarpPLS. This workshop, conducted by Dr. Jeff Hubona and myself, was fairly hands-on and interactive. Some participants had quite a great deal of expertise in PLS-SEM and WarpPLS. It was a joy to conduct the workshop!

As soon as we define the dates, we will be announcing next year’s PLS Applications Symposium. Like this years’ Symposium, it will take place in Laredo, Texas (hopefully face-to-face!), probably in the first half of April as well.

Thank you and best regards to all!

Ned Kock
Symposium Chair
https://plsas.net

Multilevel analyses in PLS-SEM: Video, article, and sample dataset

The video linked below provides an overview on how to conduct a multilevel analysis, in the context of structural equation modeling via partial least squares (PLS-SEM).

https://youtu.be/pNXI1Cz-Qkk

The article below explains how one can conduct a multilevel analysis in PLS-SEM. It employs a dataset that is very similar to the one used in the video above.

Kock, N. (2020). Multilevel analyses in PLS-SEM: An anchor-factorial with variation diffusion approach. Data Analysis Perspectives Journal, 1(2), 1-6.

A link to a PDF file is available (from the "Publications" area of WarpPLS.com):

https://scriptwarp.com/warppls/#Publications

Finally, the site area below (the "Resources" area of WarpPLS.com) provides a sample dataset available to users interested in trying the procedures discussed above: "Job performance in three companies dataset".

https://scriptwarp.com/warppls/#Resources

Enjoy!

Common method bias in PLS-SEM: Video, three articles, and sample dataset

The video linked below provides an overview on how to test for common method bias, in the context of structural equation modeling via partial least squares (PLS-SEM).

https://youtu.be/r5p0zHBqfBs

The articles below explain how one can conduct tests for common method bias in PLS-SEM. The first two articles (particularly the second) discuss the highest full collinearity variance inflation factor (FCVIF) test. The third article discusses Harman’s single factor test.

Kock, N., & Lynn, G.S. (2012). Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations. Journal of the Association for Information Systems, 13(7), 546-580.

Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1-10.

Kock, N. (2021). Harman’s single factor test in PLS-SEM: Checking for common method bias. Data Analysis Perspectives Journal, 2(2), 1-6.

Links to PDF files are available (from the "Publications" area of WarpPLS.com):

https://scriptwarp.com/warppls/#Publications

Finally, the site area below (the "Resources" area of WarpPLS.com) provides a sample dataset available to users interested in trying the tests discussed above: "Dataset with and without common method bias".

https://scriptwarp.com/warppls/#Resources

Enjoy!

Harman’s single factor test in PLS-SEM: Checking for common method bias

The article below explains how one can check for common method bias using Harman’s single factor test in the context of structural equation modeling via partial least squares (PLS-SEM).

Kock, N. (2021). Harman’s single factor test in PLS-SEM: Checking for common method bias. Data Analysis Perspectives Journal, 2(2), 1-6.

A link to a PDF file is available ().

Abstract:

Common method bias can be defined, in the context of structural equation modeling via partial least squares (PLS-SEM), as a phenomenon that is caused by the measurement method used in a study, and not by the network of causes and effects connecting the latent variables in the study. We illustrate how Harman’s single factor test of common method bias can be conducted with WarpPLS, a leading PLS-SEM software tool.

Assessing reciprocal relationships in PLS-SEM: An illustration based on a job crafting study

The article below explains how one can test reciprocal relationships in the context of structural equation modeling via partial least squares (PLS-SEM).

Morrow, D. L., & Conger, S. (2021). Assessing reciprocal relationships in PLS-SEM: An illustration based on a job crafting study. Data Analysis Perspectives Journal, 2(1), 1-5.

A link to a PDF file is available ().

Abstract:

Over the last 25 years two types of job crafting have emerged with similar quantitative measurement scales. This paper describes the process used in determining the presence of reciprocal relationships between the two job crafting constructs using WarpPLS.

Using indicator correlation fit indices in PLS-SEM: Selecting the algorithm with the best fit

The article below explains how one can use indicator correlation fit indices for selecting the analysis algorithm with the best fit in the context of structural equation modeling via partial least squares (PLS-SEM).

Kock, N. (2020). Using indicator correlation fit indices in PLS-SEM: Selecting the algorithm with the best fit. Data Analysis Perspectives Journal, 1(4), 1-4.

A link to a PDF file is available ().

Abstract:

Upon completion of a PLS-SEM analysis, one can obtain the model-implied indicator correlation matrix and compare it with the actual indicator correlation matrix. The latter is obtained directly from the data being analyzed. Indicator correlation fit indices are quantifications of the differences among these two matrices. Our focus in this paper is on the use of indicator correlation fit indices in PLS-SEM for selecting the analysis algorithm with the best fit.