title: Compound treatments and transportability of causal inference.
abstract: Ill-defined causal questions present serious problems for observational studies-problems that are largely unappreciated. This paper extends the usual counterfactual framework to consider causal questions about compound treatments for which there are many possible implementations (for example, "prevention of obesity"). We describe the causal effect of compound treatments and their identifiability conditions, with a special emphasis on the consistency condition. We then discuss the challenges of using the estimated effect of a compound treatment in one study population to inform decisions in the same population and in other populations. These challenges arise because the causal effect of compound treatments depends on the distribution of the versions of treatment in the population. Such causal effects can be unpredictable when the versions of treatment are unknown. We discuss how such issues of "transportability" are related to the consistency condition in causal inference. With more carefully framed questions, the results of epidemiologic studies can be of greater value to decision-makers.
authors.affiliation: Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA. miguel_hernan@post.harvard.edu
authors.forename: Miguel A
authors.initials: MA
authors.lastname: Hernán
authors.forename: Tyler J
authors.initials: TJ
authors.lastname: VanderWeele
mesh_terms: D015982:Bias; D015984:Causality; D003131:Combined Modality Therapy; D015986:Confounding Factors, Epidemiologic; D003657:Decision Making; D015340:Epidemiologic Research Design; D016021:Epidemiologic Studies; D005260:Female; D006801:Humans; D008297:Male; D019370:Observation; D018579:Patient Selection; D016032:Randomized Controlled Trials as Topic; D015983:Selection Bias; D012680:Sensitivity and Specificity