Learn PLS-SEM with SEMinR
A topic-by-topic video series pairing with the 2e of Partial Least Squares Structural Equation Modeling Using R (Hair, Hult, Ringle, Sarstedt, Danks & Adler, Springer). Each video ships with runnable code and walks you from model specification to publication-ready assessment.
How to use this series
Five videos walk through the full PLS-SEM workflow in teaching order, from reflective and formative measurement through the structural model to mediation and moderation. Every lesson names the textbook chapter it pairs with, and ships with a runnable R script and the slide deck from the video — plus one good R coding habit called out on screen, so you'll absorb a set of reproducibility practices without ever sitting through a style lecture.
Start with Reflective measurement if you're new to PLS-SEM, or jump straight to the topic that matches the paper you're working on. Out-of-sample prediction — PLSpredict, CVPAT, and model comparison — is covered inside the Structural model lesson.
The full PLS-SEM Using R code companion
Every chapter of the textbook as one runnable document — concise R code and its output for the complete corporate reputation workflow, from model specification through reflective and formative measurement, structural assessment, moderation, and mediation. The videos walk through subsets of this; this is the written reference you can read end-to-end or jump into chapter by chapter. The corporate reputation dataset is available from the book's companion site.
Reflective Measurement Model Assessment
Reflective measurement
Specify, estimate, and evaluate reflective constructs on the four criteria reviewers expect: indicator reliability, internal consistency, convergent validity, and discriminant validity — plus bootstrapped HTMT confidence intervals.
Formative Measurement Model Assessment
Formative measurement
Assessing formatively measured constructs: redundancy analysis for convergent validity, indicator collinearity via VIF, and interpreting outer weights and their significance.
Structural Model Assessment
Structural model
Once measurement passes, assess the structural model: path coefficients and their significance, R², f² effect sizes, Q²predict, and bootstrap confidence intervals on indirect effects.
Mediation Analysis
Mediation
Testing mediation in PLS-SEM: specific indirect effects, total indirect effects, and the Zhao, Lynch & Chen typology of full, partial, complementary, and competitive mediation.
Moderation Analysis
Moderation
Testing moderation with interaction terms in SEMinR: two-stage vs product-indicator approaches, interpreting the interaction coefficient, and visualizing simple slopes.
seminrExtras 1.0.0 — The Advanced PLS-SEM Toolkit in R
seminrExtras
seminrExtras is a companion package for seminr that ships the advanced PLS-SEM assessment methods that don't fit the base workflow — COA, NCA, NCA-ESSE, cIPMA, FIMIX-PLS, PLS-POS, CTA-PLS, PCM, CVPAT, and congruence testing. This tutorial links to a fully runnable walkthrough on the MOBI and corporate reputation datasets.