Mediation and Moderation in SEM
This course by Professor Gordon Cheung covers concepts behind mediation, moderation, and moderated-mediation with hands-on analysis and examples.
Monday 24 February 2020
Professor Gordon Cheung
This course assumes that participants have a basic of structural equation modelling and experience with using Mplus. Participants who do not possess these are strongly encouraged to attend the 2-day Introduction to Structural Equation Modelling with Mplus first.
Mediation studies are very important in studying the "why" and "how" questions of organisational phenomena and researchers have been continuously searching for the best statistical test for mediation effect.
This one-day workshop provides:
- the basic concepts behind mediation, moderation, and moderated-mediation
- review on the advantages of testing mediation and moderation effects with latent variables over observed variables
- introduction of various mediation hypotheses that can be examined in organisational studies, including the significance of specific mediation effect, comparison of the strength of two mediation effects, comparison of the strength between mediation effect and direct effect, comparison of the strength of mediation effects across groups, and moderated mediation
- Mplus syntax for testing various mediation and moderated-mediation hypotheses.
Hands-on data analysis with examples will be provided.
Cheung GW & Lau RS (In Press). Accuracy of parameter estimates and confidence intervals in moderated mediation models: A comparison of regression and latent moderated structural equations, Organizational Research Methods.
Cheung GW & Lau RS (2008). Testing mediation and suppression effects of latent variables: Bootstrapping with structural equation models, Organizational Research Methods, 11(2), 296–325.
Lau RS & Cheung GW (2012). Estimating and comparing specific mediation effects in complex latent variable models, Organizational Research Methods, 15, 3–16.
Preacher KJ, Rucker DD, Hayes AF (2007). Addressing moderated mediation hypotheses: Theory, methods and prescriptions. Multivariate Behavioral Research, 42: 185–227.