Moderated mediation plot based on User's Guide ex 3.18
Migrating from Hayes’ PROCESS to Mplus
Crosslevel interaction (twolevel moderation) plot
Twolevel mediation with random slopes
Twolevel 111 moderated mediation
Counterfactual causal effects for mediation modeling
 Muthén, B., Muthén, L. & Asparouhov, T. (2016). Regression And Mediation Analysis Using Mplus. Los Angeles: Muthén & Muthén.
 Nguyen, T.Q., WebbVargas, Y., Koning, I.K. & Stuart, E.A. (2016). Causal mediation analysis with a binary outcome and multiple continuous or ordinal mediators: Simulations and application to an alcohol intervention.
Structural Equation Modeling: A Multidisciplinary Journal, 23:3, 368383 DOI: 10.1080/10705511.2015.1062730
 De Stavola, B. L., Daniel, R. M., Ploubidis, G. B. & Micali, N. (2015). Mediation analysis with intermediate confounding: Structural equation modeling viewed through the causal inference lens.
American Journal of Epidemiology. DOI: 10.1093/aje/kwu239
 Muthén, B. & Asparouhov T. (2015). Causal effects in mediation modeling: An introduction with applications to latent variables. Structural Equation Modeling: A Multidisciplinary Journal, 22(1), 1223. DOI:10.1080/10705511.2014.935843
 Muthén, B. (2011). Applications of causally defined direct and indirect effects in mediation analysis using SEM in Mplus.
View the Technical appendix. View the Input appendix.
View Mplus inputs, data, and outputs used in this paper.
Mediation Workshop
General papers using Mplus
 McLarnon, M.J.W. & O'Neill, T.A. (2018). Extensions of auxiliary variable approaches for the investigation of mediation, moderation, and conditional effects in mixture models. Organizational Research Methods, 21(4), 955982. DOI: 10.1177/1094428118770731
 Feingold, A., MacKinnon, D.P., & Capaldi, D.M. (2018). Mediation analysis with binary outcomes: Direct and indirect effects of proalcohol influences on alcohol use disorders. Addictive Behaviors. DOI: 10.1016/j.addbeh.2018.12.018
 Asparouhov, T. & Muthén, B. (2018). Latent variable centering of predictors and mediators in multilevel and timeseries models. Structural Equation Modeling: A Multidisciplinary Journal, DOI: 10.1080/10705511.2018.1511375 (Download scripts).
 Preacher, K.J., Zhang, Z. & Zyphur, M.J. (2016). Multilevel structural equation models for assessing moderation within and across levels of analysis. Psychological Methods. 21(2), 189205. DOI: 10.1037/met0000052
 Cheung, G.W. & Lau, R.S. (2015). Accuracy of parameter estimates and confidence intervals in moderated mediation models: A comparison of regression and latent moderated structural equations.
Organazational Research Methods, 20(4) 746769. DOI: 10.1177/1094428115595869
 Wang, L., and Preacher, K. J. (2014). Moderated mediation analysis using Bayesian methods.
Structural Equation Modeling: A Multidisciplinary Journal. 22(2), 249263. DOI: 10.1080/10705511.2014.935256
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