Partial and complete mediation in path analysis in Jamovi
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In this video, I demonstrate
In this video, I demonstrate how to do a path analysis, a type of Structural Equation Modeling (SEM) using Jamovi, with a focus on Partial and complete mediation. The tutorial will guide you through the steps of conducting path analysis in Jamovi, from setting up your model to interpreting the results. We'll also cover how to examine mediation effects within the path (SEM) framework, providing you with a comprehensive understanding of how to examine the moderating effects of variables in your research.
Partial Mediation: This happens when the mediator variable only partially accounts for the relationship between the independent and dependent variables. In this scenario, the direct path from the independent variable to the dependent variable remains significant even after the mediator is controlled for. This suggests that the mediator contributes to, but does not fully explain, the effect of the independent variable on the dependent variable. Both the direct and indirect paths (through the mediator) are significant, indicating that other mechanisms alongside the mediator are also influencing the dependent variable.
Complete Mediation: This occurs when the mediator variable fully accounts for the relationship between the independent variable and the dependent variable. In this case, after controlling for the mediator, the direct path from the independent variable to the dependent variable becomes non-significant, indicating that the mediator entirely explains the influence of the independent variable on the dependent variable.
If you haven't watched our previous videos on SEM, we recommend starting from this playlist: SEM Series
Confirmatory factor analysis in AMOS ...
For further reading, check out the chapter "5. Structural Equation Modeling in Language Assessment" by Xuelian Zhu, Michelle Raquel, and Vahid Aryadoust in the book "Quantitative Data Analysis for Language Assessment Volume II Advanced Methods." This chapter provides an in-depth look at SEM in the context of language assessment. The book is available here:
https://www.routledge.com/Quantitativ...
Partial Mediation: This happens when the mediator variable only partially accounts for the relationship between the independent and dependent variables. In this scenario, the direct path from the independent variable to the dependent variable remains significant even after the mediator is controlled for. This suggests that the mediator contributes to, but does not fully explain, the effect of the independent variable on the dependent variable. Both the direct and indirect paths (through the mediator) are significant, indicating that other mechanisms alongside the mediator are also influencing the dependent variable.
Complete Mediation: This occurs when the mediator variable fully accounts for the relationship between the independent variable and the dependent variable. In this case, after controlling for the mediator, the direct path from the independent variable to the dependent variable becomes non-significant, indicating that the mediator entirely explains the influence of the independent variable on the dependent variable.
If you haven't watched our previous videos on SEM, we recommend starting from this playlist: SEM Series
Confirmatory factor analysis in AMOS ...
For further reading, check out the chapter "5. Structural Equation Modeling in Language Assessment" by Xuelian Zhu, Michelle Raquel, and Vahid Aryadoust in the book "Quantitative Data Analysis for Language Assessment Volume II Advanced Methods." This chapter provides an in-depth look at SEM in the context of language assessment. The book is available here:
https://www.routledge.com/Quantitativ...
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