Integrated structural equation modeling and causal steps in evaluating the role of the mediating variable

Area of Science:

• Social Sciences
• Statistics
• Psychometrics

Background:

• Evaluating mediating variables is crucial for understanding complex relationships in research.
• Traditional methods may not fully capture the nuances of mediation.
• An integrated approach offers a more comprehensive analytical framework.

Purpose of the Study:

• To propose and demonstrate an integrated analysis method for evaluating mediating variables.
• To combine Structural Equation Modeling (SEM) with causal steps for enhanced mediation analysis.
• To provide a validated and modifiable analytical procedure.

Main Methods:

• Integrated analysis combining SEM and causal steps.
• Conceptual model and hypotheses development.
• Validity and reliability testing using IBM SPSS Statistics 25.
• Confirmatory and regression analyses with SEM-AMOS for model modification.

Main Results:

• The integrated method successfully evaluated the role of a mediating variable.
• Model validation and modification steps ensured analytical rigor.
• The causal steps approach confirmed the mediating effect within the SEM framework.

Conclusions:

• The integrated SEM and causal steps method provides a robust framework for mediation analysis.
• This approach enhances the reliability and validity of findings related to mediating variables.
• The study validates a comprehensive procedure for complex statistical modeling.