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
Six topic videos cover the full PLS-SEM workflow, plus short SEMinR Quick Tips between releases. Every video pairs with a chapter of the textbook, a runnable R script, and one good R coding habit called out on screen — by the end of the series you'll have absorbed ten 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.
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.
Advanced Topics in PLS-SEM
Advanced
Higher-order constructs, multigroup analysis, out-of-sample prediction with PLSpredict, and cross-validated predictive ability tests (CVPAT) — the advanced toolkit for rigorous PLS-SEM in 2026.
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.