Mediation analysis via potential outcomes models.
This paper develops a causal or manipulation model framework for mediation analysis based on the concept of potential outcome. Using this framework, we provide new definitions and measures of mediation. Effects of manipulations are modeled via the linear structural model. Corresponding structural equation models (SEMs), in conjunction with two-stage least-squares estimation and the delta method, are used to perform inference. The methods are applied to data from a study of nursing interventions for postoperative pain. We address the cases of more than two treatment groups, and an interaction among mediators. For the latter, a sensitivity analysis approach to handle unidentified parameters is described. Interpretative advantages of the potential outcomes framework for mediation are emphasized.
Albert
Jeffrey M
JM
Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44120, U.S.A. jma13@case.edu
D015984:Causality; D023381:Endpoint Determination; D006801:Humans; D016014:Linear Models; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care