Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-25T05:02:33.708Z Has data issue: false hasContentIssue false
  • English
  • Français

Mediation, Moderation, and Conditional Process Analysis: Concepts, Computations, and Some Common Confusions

Part of: Current Debate in Psychology

Published online by Cambridge University Press:  14 October 2021

Juan-José Igartua Open the ORCID record for Juan-José Igartua [Opens in a new window]  and
Andrew F. Hayes Open the ORCID record for Andrew F. Hayes [Opens in a new window]
Juan-José Igartua*
Affiliation:
Universidad de Salamanca (Spain)
Andrew F. Hayes
Affiliation:
University of Calgary (Canada)
*
Correspondence concerning this article should be addressed to Juan-José Igartua. Universidad de Salamanca. Facultad de Ciencias Sociales. Departamento de Sociología y Comunicación. Campus Unamuno, Edificio FES. 37008 Salamanca (Spain). E-mail: jigartua@usal.es
Get access Rights & Permissions [Opens in a new window]

Abstract

This work provides a conceptual introduction to mediation, moderation, and conditional process analysis in psychological research. We discuss the concepts of direct effect, indirect effect, total effect, conditional effect, conditional direct effect, conditional indirect effect, and the index of moderated mediation index, while providing our perspective on certain analysis and interpretation confusions that sometimes arise in practice in this journal and elsewhere, such as reliance on the causal steps approach and the Sobel test in mediation analysis, misinterpreting the regression coefficients in a model that includes a product of variables, and subgroups mediation analysis rather than conditional process analysis when exploring whether an indirect effect depends on a moderator. We also illustrate how to conduct various analyses that are the focus of this paper with the freely-available PROCESS procedure available for SPSS, SAS, and R, using data from an experimental investigation on the effectiveness of personal or testimonial narrative messages in improving intergroup attitudes.

Keywords

conditional process analysismediation analysismoderation analysisPROCESS
Type
Research Article
Information
The Spanish Journal of Psychology , Volume 24 , 2021 , e49
Copyright
© Universidad Complutense de Madrid and Colegio Oficial de Psicólogos de Madrid 2021

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Funding Statement: This work was supported by the Ministry of Science and Innovation (Spain) to the project entitled “Narrative tools to reduce prejudice. Effects of similarity, imagined contact, empathy and narrative voice”, held by Juan-José Igartua (Grant Number CSO2015–67611–P).

Conflicts of Interest: None.

References

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Sage.Google Scholar
Álvaro, J. L., Garrido, A., Pereira, C. R., Torres, A. R., & Barros, S. C. (2019). Unemployment, self-esteem, and depression: Differences between men and women. The Spanish Journal of Psychology, 22, E1. https://doi.org/10.1017/sjp.2018.68CrossRefGoogle ScholarPubMed
Balogun, A. G., Balogun, S. K., & Onyencho, C. V. (2017). Test anxiety and academic performance among undergraduates: The moderating role of achievement motivation. The Spanish Journal of Psychology, 20, Article E14. https://doi.org/10.1017/sjp.2017.5CrossRefGoogle ScholarPubMed
Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173CrossRefGoogle ScholarPubMed
Bauer, D. J., & Curran, P. J. (2005). Probing interactions in fixed and multilevel regression: Inferential and graphical techniques. Multivariate Behavioral Research, 40, 373–400. https://doi.org/10.1207/s15327906mbr4003_5CrossRefGoogle ScholarPubMed
Blanco-Donoso, L. M., Moreno-Jiménez, B., Pereira, G., & Garrosa, E. (2019). Effects of co-worker and supervisor support on nurses’ energy and motivation through role ambiguity and psychological flexibility. The Spanish Journal of Psychology, 22, Article E25. https://doi.org/10.1017/sjp.2019.10CrossRefGoogle ScholarPubMed
Bollen, K. A. (1989). Structural equations with latent variables. John Wiley and Sons. http://doi.org/10.1002/9781118619179CrossRefGoogle Scholar
Carvalho, J. P., & Hopko, D. R. (2011). Behavioral theory of depression: Reinforcement as a mediating variable between avoidance and depression. Journal of Behavior Therapy and Experimental Psychiatry, 42(2), 154–162. https://doi.org/10.1016/j.jbtep.2010.10.001CrossRefGoogle ScholarPubMed
Caro-Cañizares, I., Díaz de Neira-Hernando, M., Pfang, B., Baca-Garcia, E., & Carballo, J. J. (2018). The strengths and difficulties questionnaire: Dysregulation profile, non-suicidal self-injury behaviors, and the mediating role of stressful life events. The Spanish Journal of Psychology, 2, E22. http://doi.org/10.1017/sjp.2018.23CrossRefGoogle Scholar
Correia, I., Salvado, S., & Alves, H. (2016). Belief in a just world and self-efficacy to promote justice in the world predict helping attitudes, but only among volunteers. The Spanish Journal of Psychology, 19, E28. https://doi.org/10.1017/sjp.2016.29CrossRefGoogle Scholar
Efron, B. (1987). Better bootstrap confidence intervals. Journal of the American Statistical Association, 82, 171–185. http://doi.org/10.1080/01621459.1987.10478410CrossRefGoogle Scholar
Edwards, J. R., & Lambert, L. S. (2007). Methods for integrating moderation and mediation: A general analytical framework using moderated path analysis. Psychological Methods, 12, 1–22. http://doi.org/10.1037/1082-989X.12.1.1CrossRefGoogle ScholarPubMed
Fairchild, A. J., & MacKinnon, D. P. (2009). A general model for testing mediation and moderation effects. Prevention Science, 10, 87–99. https://doi.org/10.1007/s11121-008-0109-6CrossRefGoogle ScholarPubMed
Fritz, M. S., Taylor, A. B., & MacKinnon, D. P. (2012). Explanation of two anomalous results in statistical mediation analysis. Multivariate Behavioral Research, 47, 61–87. http://doi.org/10.1080/00273171.2012.640596CrossRefGoogle ScholarPubMed
Gabbiadini, A., Riva, P., Andrighetto, L., Volpato, C., & Bushman, B. J. (2016). Acting like a tough guy: Violent-sexist video games, identification with game characters, masculine beliefs, & empathy for female violence victims. PLOS ONE, 11(4), Article e0152121. https://doi.org/10.1371/journal.pone.0152121CrossRefGoogle Scholar
Gonzalo Silvestre, T., & Ubillos Landa, S. (2016). Women, physical activity, and quality of life: Self-concept as a mediator. The Spanish Journal of Psychology, 19, Article E6. https://doi.org/10.1017/sjp.2016.4CrossRefGoogle ScholarPubMed
Grøntved, A., Steene-Johannessen, J., Kynde, I., Franks, P.W., Helge, J. W., Froberg, K., Anderssen, S. A., & Andersen, L. B. (2011). Association between plasma leptin and blood pressure in two population-based samples of children and adolescents. Journal of Hypertension, 29, 1093–1100. https://doi.org/10.1097/HJH.0b013e328346d787CrossRefGoogle ScholarPubMed
Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication Monographs, 76(4), 408–420. https://doi.org/10.1080/03637750903310360CrossRefGoogle Scholar
Hayes, A. F. (2015). An index and test of linear moderated mediation. Multivariate Behavioral Research, 50(1), 1–22. https://doi.org/10.1080/00273171.2014.962683CrossRefGoogle ScholarPubMed
Hayes, A. F. (2022). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (3rd Ed.). The Guilford Press.Google Scholar
Hayes, A. F., & Matthes, J. (2009). Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations. Behavior Research Methods, 41(3), 924–936. https://doi.org/10.3758/BRM.41.3.924CrossRefGoogle ScholarPubMed
Hayes, A. F., & Montoya, A. K. (2017). A tutorial on testing, visualizing, and probing interaction involving a multicategorical variable in linear regression analysis. Communication Methods and Measures, 11, 1–30. http://doi.org/10.1080/19312458.2016.1271116CrossRefGoogle Scholar
Hayes, A. F., Montoya, A. K., & Rockwood, N. J. (2017). The analysis of mechanisms and their contingencies: PROCESS versus structural equation modeling. Australasian Marketing Journal, 25, 76–81. https://doi.org/10.1016/j.ausmj.2017.02.001CrossRefGoogle Scholar
Hayes, A. F., & Preacher, K. J. (2014). Statistical mediation analysis with a multicategorical independent variable. British Journal of Mathematical and Statistical Psychology, 67(3), 451–470. https://doi.org/10.1111/bmsp.12028CrossRefGoogle ScholarPubMed
Hayes, A. F., & Rockwood, N. J. (2017). Regression-based statistical mediation and moderation analysis in clinical research: Observations, recommendations, and implementation. Behaviour Research and Therapy, 98, 39–57. https://doi.org/10.1016/j.brat.2016.11.001CrossRefGoogle Scholar
Hayes, A. F., & Rockwood, N. J. (2020). Conditional process analysis: Concepts, computation, and advances in the modeling of the contingencies of mechanisms. American Behavioral Scientist, 64(1), 19–54. https://doi.org/10.1177/0002764219859633CrossRefGoogle Scholar
Hayes, A. F., & Scharkow, M. (2013). The relative trustworthiness of inferential tests of the indirect effect in statistical mediation analysis: Does method really matter? Psychological Science, 24, 1918–1927. https://doi.org/10.1177/0956797613480187CrossRefGoogle ScholarPubMed
Holbert, R. L., & Park, E. (2020). Conceptualizing, organizing, and positing moderation in communication research. Communication Theory, 30(3), 227–246. https://doi.org/10.1093/ct/qtz006CrossRefGoogle Scholar
Igartua, J.-J., Wojcieszak, M., & Kim, N. (2019). How the interplay of imagined contact and first‐person narratives improves attitudes toward stigmatized immigrants: A conditional process model. European Journal of Social Psychology, 49(2), 385–397. https://doi.org/10.1002/ejsp.2509CrossRefGoogle Scholar
Jaccard, J., & Turrisi, R. (2003). Interaction effects in multiple regression (2nd Ed.). Sage. https://doi.org/10.4135/9781412984522CrossRefGoogle Scholar
Kenny, D. A., & Judd, C. M. (2014). Power anomolies in testing mediation. Psychological Science, 25, 334–339. http://doi.org/10.1177/0956797613502676CrossRefGoogle Scholar
Kampfer, K., Leischnig, A., Ivens, B. S., & Spence, C. (2017). Touch-flavor transference: Assessing the effect of packaging weight on gustatory evaluations, desire for food and beverages, and willingness to pay. PLOS ONE, 12(1), Article e0186121. http://doi.org/10.1371/journal.pone.0186121CrossRefGoogle ScholarPubMed
Knoster, K. C., & Goodboy, A. K. (2020). A conditional process model of academic demands and student learning. Communication Education, 69(3), 335–355. https://doi.org/10.1080/03634523.2020.1713387CrossRefGoogle Scholar
MacKinnon, D. P. (2008 ). Introduction to statistical mediation analysis. Lawrence Erlbaum AssociatesGoogle Scholar
Morgan-Lopez, A. A., & MacKinnon, D. P. (2006). Demonstration and evaluation of a method for assessing mediated moderation. Behavior Research Methods, 38, 77–89. https://doi.org/10.3758/BF03192752CrossRefGoogle ScholarPubMed
Muller, D., Judd, C. M., & Yzerbyt, V. Y. (2005). When moderation is mediated and mediation is moderated. Journal of Personality and Social Psychology, 89, 852–863. http://doi.org/10.1037/0022-3514.89.6.852CrossRefGoogle ScholarPubMed
Muralidharan, S., & Kim, E. A. (2020). Can empathy offset low bystander efficacy? Effectiveness of domestic violence prevention narratives in India. Health Communication, 35(10), 1229–1238. https://doi.org/10.1080/10410236.2019.1623645CrossRefGoogle ScholarPubMed
Navarro-Carrillo, G., Beltrán-Morillas, A. M., Valor-Segura, I., & Expósito, F. (2018). The pernicious effects of malicious versus benign envy: Perceived injustice, emotional hostility, and counterproductive behaviors in the workplace. The Spanish Journal of Psychology, 21, E41. https://doi.org/10.1017/sjp.2018.49CrossRefGoogle ScholarPubMed
O’Rourke, H. P., & MacKinnon, D. P. (2018). Reasons for testing mediation in the absence of an intervention effect: A research imperative in prevention and intervention research. Journal of Studies on Alcohol and Drugs, 79(2), 171–181. https://doi.org/10.15288/jsad.2018.79.171CrossRefGoogle ScholarPubMed
Peltonen, K., Quota, S., Sarraj, E. E., & Punamäki, R.-L. (2010). Military trauma and social development: The moderating and mediating role of peer and sibling relations in mental health. International Journal of Behavioral Development, 34(6), 554–563. https://doi.org/10.1177/0165025410368943CrossRefGoogle Scholar
Pirlott, A. G., & MacKinnon, D. P. (2016). Design approaches to experimental mediation. Journal of Experimental Social Psychology, 66, 29–38. https://doi.org/10.1016/j.jesp.2015.09.012CrossRefGoogle ScholarPubMed
Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007). Assessing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral Research, 42, 185–227. https://doi.org/10.1080/00273170701341316CrossRefGoogle Scholar
Preacher, K. J., & Selig, J. P. (2012). Advantages of Monte Carlo confidence intervals for indirect effects. Communication Methods and Measures, 6, 77–89. https://doi.org/10.1080/19312458.2012.679848CrossRefGoogle Scholar
Spencer, S. J., Zanna, M. P., & Fong, G. T. (2005). Establishing a causal chain: Why experiments are often more effective than mediational analyses in examining psychological processes. Journal of Personality and Social Psychology, 89, 845–851. https://doi.org/10.1037/0022-3514.89.6.845CrossRefGoogle ScholarPubMed
Rucker, D. D., McShane, B. B., & Preacher, K. J. (2015). A researcher’s guide to regression, discretization, and median splits of continuous variables. Journal of Consumer Psychology, 25, 666–678. https://doi.org/10.1016/j.jcps.2015.04.004CrossRefGoogle Scholar
Shrout, P. E., & Bolger, N. (2002). Mediation in experimental and nonexperimental studies: New procedures and recommendations. Psychological Methods, 7, 422–445. http://doi.org/10.1037/1082-989X.7.4.422CrossRefGoogle ScholarPubMed
Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology, 13, 290–312. http://doi.org/10.2307/270723CrossRefGoogle Scholar
Spiller, S. A., Fitzsimons, G. J., Lynch, J. G., & McClelland, G. H. (2013). Spotlights, floodlights, and the magic number zero: Simple effects tests in moderated regression. Journal of Marketing Research, 50, 277–288. https://doi.org/10.1509/jmr.12.0420CrossRefGoogle Scholar
Virkes, T., Seršić, D. M., & Lopez-Zafra, E. (2017). Core self-evaluations and individual strategies of coping with unemployment among displaced Spanish workers. The Spanish Journal of Psychology, 20, Article E59. https://doi.org/10.1017/sjp.2017.57CrossRefGoogle ScholarPubMed
Yuan, Y., & MacKinnon, D. P. (2009). Bayesian mediation analysis. Psychological Methods, 14, 301–322. http://doi.org/10.1037/a0016972CrossRefGoogle ScholarPubMed
Yzerbyt, V., Muller, D., Batailler, C., & Judd, C. M. (2018). New recommendations for testing indirect effects in mediational models: The need to report and test component paths. Journal of Personality and Social Psychology, 115, 929–943. http://doi.org/10.1037/pspa0000132CrossRefGoogle ScholarPubMed