Will PLS have to become factor-based to survive and thrive?

The article below provides an overview of various SEM approaches. It argues that minimization of type I and II errors, or false positives and negatives respectively in hypothesis testing, can only happen if latent variables are implemented as factors (and not as composites). It is argued that this requires the use of modern, factor-based PLS methods (known as PLSF methods), which have some advantages not only over classic PLS implementations, but also over covariance-based SEM approaches. We discussed a PLSF type in the article; namely type CFM3.

Kock, N. (2024). Will PLS have to become factor-based to survive and thrive? European Journal of Information Systems (forthcoming).

Link to full-text file for this article:

Will PLS have to become factor-based to survive and thrive?

Abstract:

Structural equation modelling (SEM) is a general method that aims at estimating models with latent variables (LVs), where the LVs are measured indirectly and with some imprecision via questionnaires. This is done usually employing question-statements answered on Likert-type scales. In this paper we discuss various forms of SEM, and demonstrate that composite-based models, common in classic partial least squares (PLS) implementations, are poorly aligned with the very idea of SEM. We argue that minimisation of type I and II errors, or false positives and negatives respectively in hypothesis testing, can only happen if LVs are implemented as factors (and not as composites). This requires the use of modern, factor-based PLS methods, which have some advantages not only over classic PLS implementations, but also over covariance-based SEM approaches. Our main goal with this paper is to stimulate debate, whether pro or against our views. If we are generally correct in our thinking, the impact on how quantitative research is conducted in the field of information systems, as well as many other fields, could be quite dramatic. The reason for this is the widespread use of SEM in information systems, business, and the behavioural sciences.

Note: Some readers of this blog have brought to our attention that a critique of the article above is already out, and with a number of mistakes and incorrect statements, such as that: they (the critics) used CFM1 because this is the only PLSF type documented in the WarpPLS User Manual (untrue and very easy to check); and that the algorithm that they analyzed (PLSF-CFM1) is a slow version of Dijkstra’s PLSc technique (CFM1 does not use PLSc at all); among other easy-to-avoid mistakes and incorrect statements. We are aware of this critique.

Best regards to all!

PLS Applications Symposium; 10-12 April 2024; Laredo, Texas

PLS Applications Symposium; 10-12 April 2024; Laredo, Texas
(Abstract submissions accepted until 16 February 2024)

*** 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)".

*** 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 10 April 2024 a full-day workshop on PLS-SEM will be conducted only 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.

-----------------------------------------------------------
Ned Kock
Symposium Chair
https://plsas.net

Combining sub-samples for improved statistical power in PLS-SEM: A constrained latent growth approach

The article below discusses how a researcher can combine sub-samples for improved statistical power in multigroup analyses, employing a constrained latent growth approach, in the context of structural equation modeling via partial least squares (PLS-SEM).

Cox, J. (2024). Combining sub-samples for improved statistical power in PLS-SEM: A constrained latent growth approach. Data Analysis Perspectives Journal, 5(1), 1-5.

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

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

Abstract:

Often researchers gather data that contain or can be segmented into subsamples. Therefore, sometimes a question arises as to whether the data can be treated as one sample or as several distinct samples. In this paper, I discuss how to conduct a multigroup analysis in a structural equation model with partial least squares (PLS-SEM) and demonstrate how empirical data from two different countries can be treated as one sample when using WarpPLS 8.0 to achieve higher statistical power.

Best regards to all!

Methods showcase - Using PLSF-SEM in business communication research

The article below discusses how one can employ PLSF-SEM in business communication research. The discussion is generic enough to guide the use of the method in other areas of research. PLSF-SEM builds on partial least squares (PLS) algorithms to generate correlation-preserving factors; the F refers to it being factor-based, as opposed to composite-based. A primer on the use of PLSF-SEM in business communication research is provided, based on an illustrative model inspired by motivating language theory, and where simulated data was analyzed with the software WarpPLS.

Kock, N. (2024). Methods showcase - Using PLSF-SEM in business communication research. International Journal of Business Communication (forthcoming: 23294884241233281).

Link to full-text file for this article:

Methods showcase - Using PLSF-SEM in business communication research.

Abstract:

Structural equation modeling (SEM) is a data analysis method that is widely used in business communication research, as well as research in many other fields, when scholars need to test complex models with multiple outcomes, interactions, or operations across different situations. To date, however, researchers have had to choose between using covariance-based SEM, and dealing with convergence problems; or composite-based SEM, and facing serious methodological issues. This article describes a way to combine strong aspects of both SEM types through PLSF-SEM. By utilizing this novel method, empirical researchers can employ several of the same tests traditionally used in covariance-based SEM, as well as new tests that rely on latent variable estimates, in a succinct and scholarly way. PLSF-SEM builds on partial least squares (PLS) algorithms to generate correlation-preserving factors; the F refers to it being factor-based, as opposed to composite-based. A primer on the use of PLSF-SEM in business communication research is provided, based on an illustrative model inspired by motivating language theory, and where simulated data was analyzed with the software WarpPLS.

Best regards to all!

ICIS 2023: Why I love India so much!

In a few hours I’ll be returning to the Great State of Texas from India, where I’ve been attending the ICIS 2023 Conference. I had the opportunity to meet with WarpPLS users, which I always enjoy very much, and with methodological researchers doing PLS-related work.

Talking about people doing PLS-related work, it was a special treat to be able to meet and talk with Nicholas Danks. The man is a true scholar and a genius. I hope to collaborate with him in the future, and (perhaps, if I am lucky) get some of that talent through osmosis.

Another highlight was talking again with the incomparable Dr. Boo. I was busy distracting her with nonsense when her name was mentioned at the awards ceremony. For those of you who don’t know, she is one of the forerunners of the field of Information Systems, a field that she begun influencing at the young age of 13 (according to my calculations).

This was my first time in India. I loved it so much! This was such a nice experience in no small measure due to Glory George, who was kind enough to show me some of Hyderabad. The people of India are so smart and hard working. Take for example the person on the photo below; he solved a 100-year-old numeric computing problem while riding on the back of a bike in heavy traffic!

Okay, just my imagination. But he was indeed doing what seemed to be some coding, using his friend’s constantly moving upper back as a table. By the way, if you think that traffic in India is chaotic, think again. Those who pay close attention will notice that there is method to what looks like disorderly flow. More than method actually, it is a form of art. Just don’t try driving if you are a beginner; it will be like challenging Ma Long to a “ping pong” match.

Should you want to see and hear the person who is writing this, in keeping with media naturalness theory, check this video. More views and likes will help make my dear friends Steve Harmon and Rolando Santos happy about their masterful video creation and editing work.

Best regards to all!

WarpPLS: A bit of history

The YouTube video linked below (scroll down to the end of the news article) provides a bit of history in connection with the development of WarpPLS. A big thank you to Rolando Santos for his professional video creation work!

https://www.tamiu.edu/newsinfo/2023/10/topworldresearcher10262023.shtml

Best regards to all!

Using logistic regression in PLS-SEM: Dichotomous endogenous variables

The article below discusses how one can use logistic regression with the probit approach, to avoid the problems associated with having dichotomous endogenous variables, in the context of structural equation modeling via partial least squares (PLS-SEM).

Kock, N. (2023). Using logistic regression in PLS-SEM: Dichotomous endogenous variables. Data Analysis Perspectives Journal, 4(4), 1-6.

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

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

Abstract:

A dichotomous endogenous variable would be impossible to occur at the population level, which an empirical sample is assumed to represent, because the structural error term associated with the endogenous variable is expected to be a random variable with many distinct values. Consequently, the endogenous variable is also expected to have many distinct values. This paper discusses how to address this problem, using logistic regression with the probit approach, in the context of structural equation modeling via partial least squares (PLS-SEM). Our discussion is based on an illustrative model analyzed with the software WarpPLS.

Best regards to all!