Top

Published in:

01-06-2009

A General Model for Testing Mediation and Moderation Effects

Authors: Amanda J. Fairchild, David P. MacKinnon

Published in: Prevention Science | Issue 2/2009

Abstract

This paper describes methods for testing mediation and moderation effects in a dataset, both together and separately. Investigations of this kind are especially valuable in prevention research to obtain information on the process by which a program achieves its effects and whether the program is effective for subgroups of individuals. A general model that simultaneously estimates mediation and moderation effects is presented, and the utility of combining the effects into a single model is described. Possible effects of interest in the model are explained, as are statistical methods to assess these effects. The methods are further illustrated in a hypothetical prevention program example.

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage.

Aroian, L. A. (1947). The probability function of the product of two normally distributed variables. Annals of Mathematical Statistics, 18, 265–271. doi:10.1214/aoms/1177730442.CrossRef

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, 1173–1182. doi:10.1037/0022-3514.51.6.1173.PubMedCrossRef

Bauer, D. J., Preacher, K. J., & Gil, K. M. (2006). Conceptualizing and testing random indirect effects and moderated mediation in multilevel models: New procedures and recommendations. Psychological Methods, 11, 142–163.PubMedCrossRef

Beck, C.T. (1994). Achieving statistical power through research design sensitivity. Journal of Advanced Nursing, 20, 912–916.PubMedCrossRef

Borich, G. D., & Godbout, R. C. (1974). Extreme groups designs and the evaluation of statistical power. Educational and Psychological Measurement, 34, 663–675.CrossRef

Champoux, J. E. & Peters, W. S. (1987). Form, effect size, and power in moderated regression analysis. Journal of Occupational Psychology, 60, 243–255.

Chen, H. T. (1990). Theory driven evaluations. Newbury Park, CA: Sage.

Cohen, J., Cohen, P., West, S. G., & Aiken, L. A. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed). Hillsdale, NJ: Lawrence Erlbaum Associates.

Cook, T. D., & Campbell, D. T. (1979). Quasi-experimentation: Design and analysis issues for field settings. Chicago: Rand McNally.

Dearing, E., & Hamilton, L. C. (2006). Contemporary advances and classic advice for analyzing mediating and moderating variables. Monographs of the Society for Research in Child Development, (December), 71, 88–104.

Donaldson, S. I. (2001). Mediator and moderator analysis in program development. In S. Sussman (Ed.), Handbook of program development for health and behavior research and practice (pp. 470–496). Thousand Oaks, CA: Sage.

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. doi:10.1037/1082-989X.12.1.1.PubMedCrossRef

Evans, M. G. (1985). A Monte Carlo study of the effects of correlated method variance in moderated multiple regression analysis. Organizational Behavior and Human Decisions Processes, 36, 305–323.CrossRef

Fairchild, A. J. (2008). A comparison of frameworks for the joint analysis of mediation and moderation effects. Unpublished doctoral dissertation. Arizona State University, Tempe.

Frazier, P. A., Tix, A. P., & Barron, K. E. (2004). Testing moderator and mediator effects in counseling psychology research. Journal of Counseling Psychology, 51, 115–134. doi:10.1037/0022-0167.51.1.115.CrossRef

Gogineni, A., Alsup, R., & Gillespie, D. (1995). Mediation and moderation in social work research. Social Work Research, 19, 57–63.PubMed

Holland, P. W. (1988). Causal inference, path analysis, and recursive structural equations models. Sociological Methodology, 18, 449–484. doi:10.2307/271055.CrossRef

Hoyle, R. H., & Robinson, J. C. (2003). Mediated and moderated effects in social psychological research: Measurement, design, and analysis issues. In C. Sansone, C. Morf, & A. T. Panter (Eds.), Handbook of methods in social psychology (pp. 213–233). Thousand Oaks, CA: Sage.

James, L. R., & Brett, J. M. (1984). Mediators, moderators, and tests for mediation. The Journal of Applied Psychology, 69, 307–321. doi:10.1037/0021-9010.69.2.307.CrossRef

Judd, C. M., & Kenny, D. A. (1981a). Process analysis: Estimating mediation in treatment evaluations. Evaluation Review, 5, 602–619. doi:10.1177/0193841X8100500502.CrossRef

Judd, C. M., & Kenny, D. A. (1981b). Estimating the effects of social intervention. Cambridge, England: Cambridge University Press.

Kenny, D. A., Korchmaros, J. D., & Bolger, N. (2003). Lower level mediation in multilevel models. Psychological Methods, 8, 115–128.PubMedCrossRef

MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. Mahwah, NJ: Earlbaum.

MacKinnon, D. P., & Dwyer, J. H. (1993). Estimating mediated effects in prevention studies. Evaluation Review, 17, 144–158. doi:10.1177/0193841X9301700202.CrossRef

MacKinnon, D. P., Fritz, M. S., Williams, J., & Lockwood, C. M. (2007). Distribution of the product confidence limits for the indirect effect: Program PRODCLIN. Behavior Research Methods, 39, 384–389.PubMed

MacKinnon, D. P., Krull, J. L., & Lockwood, C. M. (2000). Equivalence of the mediation, confounding, and suppression effect. Prevention Science, 1, 173–181. doi:10.1023/A:1026595011371.PubMedCrossRef

MacKinnon, D. P., & Lockwood, C. M. (2001). Distribution of product tests for the mediated effect: Power and Type I error rates. Unpublished manuscript.

MacKinnon, D. P., Lockwood, C. M., & Hoffman, J. M. (1998, June). A new method to test for mediation. Paper presented at the annual meeting of the Society for Prevention Research, Park City, UT.

MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M., West, S. G., & Sheets, V. (2002). A comparison of methods to test the significance of mediation and other intervening variable effects. Psychological Methods, 7, 83–104. doi:10.1037/1082-989X.7.1.83.PubMedCrossRef

MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39, 99–128. doi:10.1207/s15327906mbr3901_4.CrossRef

McClelland, G. H. & Judd, C. M. (1993). Statistical difficulties of detecting interactions and moderator effects. Psychological Bulletin, 114, 376–390.PubMedCrossRef

Morgan-Lopez, A. A., & MacKinnon, D. P. (2006). Demonstration and evaluation of a method for assessing mediated moderation. Behavior Research Methods, 38, 77–87.PubMed

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. doi:10.1037/0022-3514.89.6.852.PubMedCrossRef

Preacher, K. J., Rucker, D. D., & Hayes, R. F. (2007). Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral Research, 42, 185–227.

Rose, B. M., Holmbeck, G. N., Coakley, R. M., & Franks, E. A. (2004). Mediator and moderator effects in developmental and behavioral pediatric research. Journal of Developmental and Behavioral Pediatrics, 25, 58–67. doi:10.1097/00004703-200402000-00013.PubMedCrossRef

Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology, 13, 290–312. doi:10.2307/270723.CrossRef

Sobel, M. E. (1986). Some new results on indirect effects and their standard errors in covariance structure models. Sociological Methodology, 16, 159–186. doi:10.2307/270922.CrossRef

Tein, J., Sandler, I. N., MacKinnon, D. P., & Wolchik, S. A. (2004). How did it work? Who did it work for? Mediation in the context of a moderated prevention effect for children of divorce. Journal of Consulting and Clinical Psychology, 72, 617–624. doi:10.1037/0022-006X.72.4.617.PubMedCrossRef

Wegener, D. T., & Fabrigar, L. R. (2000). Analysis and design for nonexperimental data addressing causal and noncausal hypotheses. In H. T. Reis & C. M. Judd (Eds.), Handbook of research methods in social and personality psychology (pp. 412–450). New York: Cambridge University Press.

West, S. G., & Aiken, L. S. (1997). Toward understanding individual effects in multiple component prevention programs: Design and analysis strategies. In K. Bryant, M. Windle, & S. West (Eds.), The science of prevention: Methodological advances from alcohol and substance abuse research (pp. 167–209). Washington, DC: American Psychological Association.CrossRef

Yzerbyt, V. Y., Muller, D., & Judd, C. M. (2004). Adjusting researchers’ approach to adjustment: On the use of covariates when testing interactions. Journal of Experimental Social Psychology, 40, 424–431. doi:10.1016/j.jesp.2003.10.001.CrossRef

Title: A General Model for Testing Mediation and Moderation Effects
Authors: Amanda J. Fairchild
David P. MacKinnon
Publication date: 01-06-2009
Publisher: Springer US
Published in: Prevention Science / Issue 2/2009
Print ISSN: 1389-4986
Electronic ISSN: 1573-6695
DOI: https://doi.org/10.1007/s11121-008-0109-6

At a glance: The STEP trials

Springer Medicine

A General Model for Testing Mediation and Moderation Effects

Abstract

At a glance: The STEP trials

Springer Medicine

Abstract

Please log in to get access to this content

Other articles of this Issue 2/2009

Pubertal Timing, Friend Smoking, and Substance Use in Adolescent Girls

Educational Success and Adult Health: Findings from the Chicago Longitudinal Study

Do Predictors of the Implementation Quality of School-Based Prevention Programs Differ by Program Type?

Altering School Climate through School-Wide Positive Behavioral Interventions and Supports: Findings from a Group-Randomized Effectiveness Trial

Does the Type of CIA Policy Significantly Affect Bar and Restaurant Employment in Minnesota Cities?

Psychosocial Mediators of a School-Based Tobacco Prevention Program in India: Results from the First Year of Project MYTRI