Bradly Perkins

           One of the most advanced quantitative methods applied to criminal justice data is mediation and moderation analysis. Hayes (2014) describes a mediation model as linking a disciplinary cause (X) to an apparent effect (Y) at a minimum due in part to a “mediator” variable (M). The author promotes this theory as XàMàY, describing it as a contributory set of events. He states that the mediator variable can be any tenable “mechanism” that would allow X to apply an effect to Y; however, he stresses how this effect must be influential. The other aspect of the advanced quantitative method is moderation. Hayes describes moderation as the effect of X on Y if the effect’s size or direction is reliant upon M. He states how this explains the conditions that hasten, block, or magnify the effect. The author elaborates by explaining that it also describes the what or whom the effect is in terms of size, included or not, and other descriptors. Continuing, he shares that this can be phrased as M being the moderator of the X →Y relationship or that X and M collaborate on their influence on Y.

Advantages of Applying the Analysis

           The advantage of applying mediation and moderation analysis is that researchers can study relationships in greater depth than merely simple relationship analysis to garner a bigger picture of real-world events, transactions, and other noteworthy items. For example, Islam et al. (2020) conducted a study investigating the mechanisms between work-family conflict and job dissatisfaction among law enforcement officers when considering the threat to a family role as a mediator and role segment enhancement as a moderator. In their study, they were able to determine how the mediating role of threat to the family role contributes to the source attribution perspective, which assumes that when a person perceives their work role as disturbing their family role, the person starts to view their work role as unfavorable since it is seen as a threat to their family role, which subsequently leads to job dissatisfaction. In the study conducted by Hu et al. (2018), the researchers uncovered how kindergarteners' attitudes toward reading could fully mediate the effect of emotional support, rather than classroom organization or instructional support, on Chinese vocabulary. Their study also found how the present findings reflected that different domains of the class could influence the developmental outcomes together without the ability to apply mediation and moderation analysis to study the impact of how these relations appear in the real world.

Issues with Analysis

           Memon et al. (2018) discuss one issue that resides with this form of analysis many postgraduate researchers are unaware of the requirements and considerations for analyzing a mediation framework. They uncovered how many questions have been posed surrounding mediation analysis, including direct and indirect effects, many hypotheses, interpretation of results, type of approach, and selection of appropriate analytical tools. There is an overwhelming tendency for the student tend to use outdated methods and approaches, as the author share. The authors further discovered that many students tended to use multiple mediators. The use of the multiple mediators made the research modeling extremely complex and unnecessary. Memon et al. explain how the need for a mediator in a model must be brought forth and justified in the beginning phases. The authors suggest that the researcher ask themselves essential questions. The first question they raise is why a mediator is needed, with the second being which variable should be the mediator and why to select it. As the authors explain, conceptualizing the mediation relationship must be considered carefully when examining the relationships between the variables of interest and the theoretical meaning behind those relationships. Without this forethought, the design and results will be flawed. Finally, they explain how focusing solely on statistical issues, and data analysis tools are also insufficient to justify a mediation study.

Conclusion

            “You were running well. Who hindered you from obeying the truth? This persuasion is not from him who calls you. A little leaven leavens the whole lump” (English Standard Version Bible, 1952/2001, Galatians 5:7-9). The same could be said about flawed analysis. “And he said to them, ‘The harvest is plentiful, but the laborers are few. Therefore pray earnestly to the Lord of the harvest to send out laborers into his harvest’” (Luke 10:2). In the previous verse, there are two variables mentioned, harvest and laborers, with the mediator being prayer and the impact that prayer would have on the harvest. In other words, a Biblical mediation and moderation analysis. By examining the advantages and issues surrounding mediation and moderation analysis, this post sought to describe one of the most advanced quantitative methods applied to criminal justice data. The analysis is powerful; however, one must be mindful of the issues that surround using mediation and moderation analysis and not simply use the analysis because one knows of the analysis.

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