Deidra
Sure, Deidra! These are confusing and complex statistical terms; one way to think of them is as "third" variables. Research questions that ask how, when, for whom, which, and under what conditions require attention to additional (“third”) variables that can explain how two variables are related. Mediation and moderation are two examples of this detailed examination of relations between variables (Kraemer, Kiernan, Essex, & Kupfer, 2008). There has been a great deal of interest in third variable analyses because they offer the potential to provide a more sophisticated understanding of interdependencies.
Mediation is defined as a relation such that an independent variable causes a mediating variable, which then causes a dependent variable (MacKinnon, 2008). For mediation to exist, the following conditions must be met. First, there must be a substantial relation between an independent variable and the mediating variable, and there must be a relation between the mediating variable and the dependent variable when accounting for the independent variable. Second, by definition, mediation requires a causal precedence such that the independent variable precedes and is a cause of the mediator, and the mediator must precede and be a cause of the dependent variable. Ideally, repeated measures of the mediator and dependent variable are available to investigate temporal relations, but often these causal relations must be inferred based on theory or prior research.
As an example, Barerra, Strycker, MacKinnon, and Toobert (2008) use analyses of mediation to evaluate the mechanisms by which the Mediterranean Lifestyle Program facilitates lifestyle modifications for patients with diabetes. Their approach evaluates if the intervention is successful in bringing about change in social-ecological resources (putative mediators), and if increased social-ecological resources then predict improved health behaviors. Such an approach facilitates refinement of the program by building on active components and either modifying or minimizing components that appear less effective in bringing about the desired effects.
In contrast, an examination of moderating factors considers the unique conditions under which two variables are related. A moderator variable is one in which the relation between the independent variable and dependent variable changes across levels of the moderator. Although often confused with mediation, a moderator is not intermediate in the causal sequence from the IV to the DV. Moderators are included in statistical models as an interaction term. For the assessment of moderation effects, the relation between the independent and dependent variable must be different at different levels of a third variable. When the third variable is a grouping variable, then the relation between the independent and dependent variable is simply different between the two groups, for example, if the relation differs for males and females.
Analyses of moderation are useful for asking questions such as “When is stress dangerous to one’s health?”; “Under what conditions are hostile people at greatest risk?” and “For whom is this intervention effective?”
One other type of third variable is a covariate, which has a relation with one or both of the independent and dependent variables, but does not appreciably change the relation between an independent and dependent variable when included in a statistical analysis. Covariates are generally not of theoretical interest, but are often included in a model to explain additional variability in a dependent variable. For example, Vella et al. (2008) include a number of covariates, including posture, caffeine intake, and body mass index, in their analyses of the influence of hostility and social interactions on ambulatory blood pressure.
*Much of the info for today's post came from MacKinnon and Luecken (2008). Next time I will post an updated blog index. Do you have an issue or a question that you would like me to discuss in a future post? Would you like to be a guest writer? Send me your ideas! leann.stadtlander@waldenu.edu
Barerra, M., Strycker, L.A., MacKinnon, D.P., & Toobert, D.J. (2008). Social-ecological resources as mediators of two-year diet and physical activity outcomes in Type 2 Diabetes patients. Health Psychology, 27(2):S118–S125.
Kraemer, H.C., Kiernan, M., Essex, M., & Kupfer, D.J. (2008). How and why criteria defining moderators and mediators differ between the Baron & Kenny and MacArthur approaches. Health Psychology, 27(2):S101–S108.
MacKinnon, D.P. (2008). Introduction to statistical mediation analysis. Erlbaum: Mahwah, NJ;
MacKinnon, D.P. & Luecken, L.J. (2008). How and for Whom? Mediation and Moderation in Health Psychology. Health Psychology, 27(2 Suppl), S99.
Vella, E.J., Kamarck, T.W., & Shiffman, S. (2008). Hostility moderates the effects of social support and intimacy on blood pressure in daily social interactions. Health Psychology, 27(2):S155–S162.
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