PLS-SEM — Topic Summaries
AI-powered summaries of 9 videos about PLS-SEM.
9 summaries
What is R Square, F Square, and Q Square in PLS-SEM (SmartPLS)
R square, F square, and Q square are three PLS-SEM metrics that answer different questions about a structural model: how much variance the model...
Necessary Condition Analysis (NCA) using PLS-SEM in #SmartPLS4
Necessary Condition Analysis (NCA) in SmartPLS4 lets researchers identify “must-have” predictors—factors that set a minimum threshold required for an...
The Concept and Theory of Moderation Analysis in PLS-SEM
Moderation analysis in PLS-SEM is built for one core problem: relationships between two constructs often change depending on a third variable. That...
32. SEMinR Lecture Series - Multi-group Analysis (PLS-MGA)
Multi-group analysis in SEMinR (PLS-MGA) lets researchers test whether key path relationships in a PLS-SEM model hold the same across subgroups—here,...
20. SEMinR Series. Evaluating Structural Model | Step 1 | Collinearity Diagnostics
After finishing reliability/validity checks for the measurement (outer) models, the next priority in PLS-SEM is to evaluate the structural (inner)...
16. SEMinR Lecture Series | Evaluating Formative Measurement Model | Introduction
Formative measurement models in SEMinR (PLS-SEM) require a different evaluation workflow than reflective ones, and the practical difference starts at...
Data Distribution/Normality in PLS SEM using SmartPLS
PLS-SEM work in SmartPLS often raises a practical question: should researchers test whether survey responses are normally distributed? The core...
Differences between CBSEM, PLSSEM, and GSCA
Generalized Structured Component Analysis (GSCA) is the newest addition discussed here, and it stands out for how it fits data: it minimizes...
What if the condition is not necessary? NCA using PLS-SEM in #SmartPLS4
Necessary Condition Analysis (NCA) in SmartPLS-SEM is often framed around whether an antecedent’s presence is required for an outcome. This session...