Structural Equation Modelling using SEMinR
A detailed lecture series on how to conduct Partial Least Squares Structural Equation Modelling (PLS-SEM) using R Package SEMinR
Learn PLS-SEM Structural Equation Modelling using SEMinR
SEMinR brings a friendly syntax to creating and estimating structural equation models (SEM). The syntax allows applied practitioners of SEM to use terminology that is very close to their familiar modeling terms (e.g., reflective, composite, interactions) instead of specifying underlying matrices and covariances. SEM models can be estimated either using Partial Least Squares Path Modeling (PLS-PM) as popularized by SmartPLS, or using Covariance Based Structural Equation Modeling (CBSEM) as popularized by LISREL and AMOS. Confirmatory Factor Analysis (CFA) of reflective measurements models is also supported. Both CBSEM and CFA estimation use the Lavaan package.
- A natural feeling, domain-specific language to build and estimate structural equation models in R
- Can use variance-based PLS estimation and covariance-based SEM estimation to model composite and common-factor constructs
- High-level functions to quickly specify interactions, higher order constructs, and structural paths
SEMinR uses its own PLS-PM estimation engine and integrates with the Lavaan package for CBSEM/CFA estimation. It also brings a few methodological advancements not found in other packages or software, and encourages best practices wherever possible.
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PLS-SEM using SEMinR
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01. SEMinR Lectures Series: Partial Least Squares Structural Equation Modelling (PLS-SEM) in R
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02. SEMinR Lecture Series - Introduction to SEMinR, R and R Studio
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03. SEMinR Lecture Series | Create Project, Load, and Inspect the Data
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04. SEMinR Lecture Series | Specifying the Measurement Model | PLS-SEM in R
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05. SEMinR Lecture Series | Specifying the Structural Model | PLS-SEM in R
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06. SEMinR. Review of Model Specification, Composites, Modes (A/B), and Weighting Schemes
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07. SEMinR Lecture Series | PLS Model Estimation and Generating Summary Output
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08. SEMinR Lecture Series. Bootstrapping the PLS Model and generating Summary Results
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09. SEMinR Lecture Series - Single Item Measure, Compare Results with SmartPLS, and Case Sensitivity
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10. SEMinR Lecture Series | Print, Export, and Plot PLS-SEM Results
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11. SEMinR Series - Review of SEMinR Package | Measurement and Structural Model with Summary Output
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12. SEMinR Lecture Series - Evaluating Reflective Measurement Model - Step 1: Indicator Reliability
Addtional Research Sections
- 10 Minute Research Methodology
- Data Analysis using SmartPLS3
- Data Analysis using SPSS
- How to Search for a Research Topic
- How to Write for High Impact Factor Journals
- Quick Guides to Research
- Searching and Writing the Literature Review
- SmartPLS4 Tutorials Series
- Social Sciences Research Tutorials
- SPSS AMOS Software for SEM
- SPSS Hayes Process Macro Lecture Series
- Understanding the Research Methodology