STRUCTURAL EQUATION MODELLING (SEM)
Structured data makes up around 20% of the world’s data and is organised in rows and columns, making it ideal for statistical analysis and model testing.
Why SEM
Structural Equation Modelling is a powerful statistical technique used to analyse structural relationships between measured variables and latent constructs. At Treanalytics, we use AMOS for covariance-based SEM and SmartPLS for variance-based SEM, allowing flexibility depending on your research goals and data characteristics.
With SEM, we can simultaneously assess measurement models (validity and reliability of constructs) and structural models (testing hypotheses among variables), making it ideal for theory testing, model development, and academic publications. Whether you need confirmatory factor analysis, path analysis, or mediation/moderation testing, we deliver results that meet the highest academic standards. Book a free meeting with our consultants and they will guide you on the steps to follow.
Our SEM analysis includes:
Detailed explanation of the data analysis process
Descriptive analysis
Normality test
Measurement Model Analysis
- Confirmatory factor analysis (CFA)
- Reliability analysis (Cronbach’s Alpha, Composite reliability coefficients)
- Convergent validity (factor loadings and AVE)
- Discriminant validity analysis (Fornell and Larcker’s criterion & Hetero-Trait Mono-Trait (HTMT)
- Detailed explanations of the measures applied to improve the CFA model
Structural model analysis
- Structural Equation Modelling with control Variables
- Structural Equation Modelling using a covariance-based approach
- Structural Equation Modelling using a component-based approach
- Common Method Bias
- Multigroup Analysis
- Mediation Analysis
- Moderation Analysis
- Moderation Slop Analysis
- Mediated Moderation Analysis
- Moderated Mediation Analysis
- Second & third Order Reflexive SEM Analysis
Clear interpretation of the SEM results
Detailed & comprehensive report delivered after analysis
