Synthesizing results of multiple randomized experiments to establish causality in mediation testing

• Mediation is defined as transfer of causality from X to Y via the mediator, M.
• Classic mediation analysis tests mediation without manipulating the mediator.
• We propose manipulating X and M in separate sets of experiments.
• Then use meta-analysis to synthesize each set of experiments.
• We provide an example based on Pygmalion field experiments.

Mediation has to do with the transfer of causality from an independent variable to a dependent variable via a third variable called a “mediator.” Because the experimental method is the universally recognized gold standard for establishing causality, we propose that conducting two experiments, one manipulating the independent variable and another manipulating the hypothesized mediator, most rigorously tests mediation hypotheses. When there are several experiments in which the independent variable was manipulated and also several experiments in which the mediator was manipulated, synthesizing these two sets of experiments using meta-analysis yields the ultimate mediation evidence. If these experiments were conducted in the field, both internal validity and external validity would be maximized. An example of the synthesis of multi-experiment mediation tests is provided and its potential and limitations are discussed.