Table 5.
Overview of the way each method for statistical mediation analysis handles other types of data situations.
| Situation | Ordinary least square regression | Structural equation modeling | Potential outcomes frameworka |
|---|---|---|---|
| Handling of missing data | Listwise deletion by default. Other missing data techniques can be applied manually. | Listwise deletion by default. Full-information maximum likelihood is facilitated. | Listwise deletion by default. Multiple imputation can be applied manually. |
| Inclusion of constructs measured by multiple variables | As a sum score, factor score, or computed index. | As a latent variable through factor analysis, controlling for measurement error. | As a sum score, factor score or computed index. |
| Multiple mediator models | Separate estimation the indirect through each mediator variable. | Simultaneous estimation of all indirect effects in the mediation model. | Provides an estimate of the total indirect effect through all mediator variables combined. |
| Dichotomous mediator and/or outcome variable | Fit logistic regression models instead of OLS regression models. Standardization of the coefficients before estimating the indirect effect is advised when the mediator and outcome are both dichotomous. |
Fit equations (1), (2), (3) as logistic regressions instead of linear regressions. Standardization of the coefficients before estimating the indirect effect is advised when the mediator and outcome are both dichotomous. |
Replace OLS regression models with logistic regression models. Only use when the outcome prevalence is lower than 10%. |
| Multilevel and longitudinal data | Replace OLS regression models with multiple linear mixed models. | Use multilevel SEM. | Replace OLS regression models with multiple linear mixed models. |
OLS: ordinary least square; SEM: structural equation modeling.
More information on the way the three methods handle these situations can be found in the references in the text.
a
Based on the way the R package ‘mediation’ handles these situations, which may deviate from the way the SAS, STATA, and SPSS macros handle these situations.