Mediation is a statistical method that examines the relationship between an independent variable (IV) and a dependent variable (DV) through a mediator variable (MV). The MV is a variable influenced by the IV, which, in turn, influences the DV. Mediation analysis can be conducted using various statistical methods, including regression analysis, structural equation modeling, and path analysis (Ten Have & Joffe, 2012).
Using mediation in my project:
Mediation can be used in several ways in my doctoral project about construction pollution. For example, I could use mediation to:
- Identifying the underlying causes of construction pollution: I can employ mediation analysis to explore the root causes of construction pollution. In this context, the independent variable (IV) would represent the type of construction activity, the mediator variable (MV) would capture the amount of pollution emitted, and the dependent variable (DV) would signify the negative environmental impact (Bind et al., 2014). Through mediation analysis, I can discern the specific pathways by which different construction activities contribute to pollution and the extent to which this pollution adversely affects the environment.
- Developing and implementing strategies to mitigate construction pollution: Mediation analysis can also be utilized to formulate effective pollution reduction strategies. In this case, the IV would pertain to the type of construction activity, the MV would reflect the amount of pollution emitted, and the DV would indicate the effectiveness of various pollution mitigation strategies (Hüls et al., 2018). I can identify the most productive approach for reducing pollution associated with different construction activities by applying mediation analysis.
- Evaluating the effectiveness of policies and regulations designed to reduce construction pollution: Mediation analysis can contribute to assessing the efficacy of policies and regulations aimed at curbing construction pollution. Here, the IV would represent the specific policy or regulation, the MV would represent the amount of pollution emitted, and the DV would indicate the effectiveness of the policy or regulation in reducing pollution (Lou et al., 2023). Through mediation analysis, I can discern which policies and regulations most successfully mitigate pollution stemming from construction activities.
Example in my research:
For a more specific example within my research project, suppose I am examining the impact of construction pollution on air quality in a particular community. I could employ mediation analysis to investigate the relationship between the type of construction activity (IV), the amount of pollution emitted (MV), and the resulting change in air quality (DV). The mediation analysis would allow me to identify the distinct mechanisms by which various construction activities contribute to pollution and the degree to which this pollution affects air quality.
Conclusion
Mediatifor understanding can be used to understand the complex relationship variables. It can be used to identify the causal paths that lead to outcomes and to assess the relative importance of different variables in predicting outcomes. By using mediation analysis in my research project, I can better understand the causes and effects of construction pollution and develop more effective strategies to reduce pollution and protect the environment.
References
Bind, M. A., Lepeule, J., Zanobetti, A., Gasparrini, A., Baccarelli, A. A., Coull, B. A., ... & Schwartz, J. (2014). Air pollution and gene-specific methylation in
the Normative Aging Study: association, effect modification, and mediation analysis. Epigenetics, 9(3), 448-458.
Hüls, A., Vierkötter, A., Sugiri, D., Abramson, M. J., Ranft, U., Krämer, U., & Schikowski, T. (2018). The role of air pollution and lung function in cognitive
impairment. European Respiratory Journal, 51(2).
Lou, X., Zhi, F., Sun, X., Wang, F., Hou, X., Lv, C., & Hu, Q. (2023). Construction of co-immobilized laccase and mediator based on MOFs membrane for
enhancing organic pollutants removal. Chemical Engineering Journal, 451, 138080.
Ten Have, T. R., & Joffe, M. M. (2012). A review of causal estimation of effects in mediation analyses. Statistical Methods in Medical Research, 21(1), 77-
107.