title: Generalizing Study Results: A Potential Outcomes Perspective.
abstract: Great care is taken in epidemiologic studies to ensure the internal validity of causal effect estimates; however, external validity has received considerably less attention. When the study sample is not a random sample of the target population, the sample average treatment effect, even if internally valid, cannot usually be expected to equal the average treatment effect in the target population. The utility of an effect estimate for planning purposes and decision making will depend on the degree of departure from the true causal effect in the target population due to problems with both internal and external validity. Herein, we review concepts from recent literature on generalizability, one facet of external validity, using the potential outcomes framework. Identification conditions sufficient for external validity closely parallel identification conditions for internal validity, namely conditional exchangeability; positivity; the same distributions of the versions of treatment; no interference; and no measurement error. We also require correct model specification. Under these conditions, we discuss how a version of direct standardization (the g-formula, adjustment formula, or transport formula) or inverse probability weighting can be used to generalize a causal effect from a study sample to a well-defined target population, and demonstrate their application in an illustrative example.
authors.affiliation: From the aDepartment of Epidemiology, University of North Carolina, Chapel Hill, NC; bDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; cDepartment of Biostatistics, University of North Carolina, Chapel Hill, NC; and dDepartment of Biostatistics and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.
authors.forename: Catherine R
authors.initials: CR
authors.lastname: Lesko
authors.forename: Ashley L
authors.initials: AL
authors.lastname: Buchanan
authors.forename: Daniel
authors.initials: D
authors.lastname: Westreich
authors.forename: Jessie K
authors.initials: JK
authors.lastname: Edwards
authors.forename: Michael G
authors.initials: MG
authors.lastname: Hudgens
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Cole
mesh_terms: D015982:Bias; D015984:Causality; D004812:Epidemiologic Methods; D005260:Female; D006801:Humans; D008297:Male; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D013223:Statistics as Topic; D014481:United States