Related Experiment Video
Updated: Aug 2, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
A perspective on using partial least squares structural equation modelling in data articles
Christian M Ringle1, Marko Sarstedt2,3, Noemi Sinkovics4
1Hamburg University of Technology, Department of Management Sciences and Technology, Hamburg, Germany.
Abstract:
This perspective article on using partial least squares structural equation modelling (PLS-SEM) is intended as a guide for authors who wish to publish datasets that can be analysed with this method as stand-alone data articles. Stand-alone data articles are different from supporting data articles in that they are not linked to a full research article published in another journal. Nevertheless, authors of stand-alone data articles will be required to clearly demonstrate and justify the usefulness of their dataset. This perspective article offers actionable recommendations regarding the conceptualisation phase, the types of data suitable for PLS-SEM and quality criteria to report, which are generally applicable to studies using PLS-SEM. We also present adjusted versions of the HTMT metric for discriminant validity testing that broaden its applicability. Further, we highlight the benefit of linking data articles to already published research papers that employ the PLS-SEM method.
More Related Videos
Related Concept Videos
Mechanistic Models: Compartment Models in Individual and Population Analysis
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Calibration Curves: Linear Least Squares
For data that follow a straight line, the standard method for fitting is the linear...
Residuals and Least-Squares Property
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:

