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Thursday, January 21, 2021

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.

Tuesday, November 10, 2020

PLS Applications Symposium; 14 - 16 April 2021; Laredo, Texas


PLS Applications Symposium; 14 - 16 April 2021; Laredo, Texas

(Abstract submissions accepted until 15 February 2021)

*** 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 14 April 2021 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 

Saturday, October 17, 2020

Testing mediation via indirect effects in PLS-SEM: A social networking site illustration


The article below explains how one can conduct a comprehensive mediation analysis via indirect effects in the context of structural equation modeling via partial least squares (PLS-SEM).

Moqbel, M., Guduru, R., & Harun, A. (2020). Testing mediation via indirect effects in PLS-SEM: A social networking site illustration. Data Analysis Perspectives Journal, 1(3), 1-6.

A link to a PDF file is available ().

Abstract:

Mediation analysis, in the context of structural equation modeling via partial least squares (PLS-SEM), affords a better understanding of the relationships among independent and dependent variables, when the variables seem to not have a definite connection. In this paper, we demonstrate such an analysis in the context of social networking sites, using WarpPLS, a leading PLS-SEM software tool.

Sunday, September 13, 2020

Adding high-quality WarpPLS graphs into Word files

To add high-quality WarpPLS graphs to Word papers, try the following steps:

- Copy the graph to the clipboard.

- Open with Paint. 

- Crop and save as .png.

- Import into Word. 

The .png can also be edited prior to importing, or used in .ppt or .pptx drawings. 

The paper linked below illustrates the final results, which are arguably very good - see figs. 1 and 2.

Kock, N. (2016). Advantages of nonlinear over segmentation analyses in path models. International Journal of e-Collaboration, 12(4), 1-6.

Saturday, August 1, 2020

Multilevel analyses in PLS-SEM: Article, video, and sample dataset


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

Kock (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 ().

Abstract:

A multilevel analysis, in the context of structural equation modeling via partial least squares (PLS-SEM), can be seen as an analysis in which: (a) data is collected at the individual level from multiple groups, and (b) group membership is expected to influence data analysis results. In this paper we illustrate such an analysis employing WarpPLS, a leading PLS-SEM software tool. The analysis employs an anchor-factorial with variation diffusion approach.

The short video linked below provides an overview on how to conduct multilevel analyses in PLS-SEM.

https://youtu.be/pNXI1Cz-Qkk

Finally, the site below provides a sample dataset: "Job performance in three companies dataset". This dataset is available under the "Resources" area.

https://warppls.com

Enjoy!

Monday, July 27, 2020

Multilevel analyses in PLS-SEM


Dear colleagues:

The short video linked below provides an overview on how to conduct multilevel analyses in PLS-SEM.

https://youtu.be/pNXI1Cz-Qkk

Enjoy!

Saturday, May 30, 2020

How time series data can be analyzed with PLS-SEM


Dear colleagues:

The short video linked below, on how to predict the price of bitcoin, is for those who want to understand how time series data can be analyzed with PLS-SEM.

https://youtu.be/8nTLYH-4uWM

Enjoy!