Target Validity: Bringing Treatment of External Validity in Line with Internal Validity
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EPIDEMIOLOGIC METHODS (P HOWARDS, SECTION EDITOR)
Target Validity: Bringing Treatment of External Validity in Line with Internal Validity Catherine R. Lesko 1
&
Benjamin Ackerman 2 & Michael Webster-Clark 3 & Jessie K. Edwards 3
# Springer Nature Switzerland AG 2020
Abstract Purpose of Review “Target bias” is the difference between an estimate of association from a study sample and the causal effect in the target population of interest. It is the sum of internal and external bias. Given the extensive literature on internal validity, here, we review threats and methods to improve external validity. Recent Findings External bias may arise when the distribution of modifiers of the effect of treatment differs between the study sample and the target population. Methods including those based on modeling the outcome, modeling sample membership, and doubly robust methods are available, assuming data on the target population is available. Summary The relevance of information for making policy decisions is dependent on both the actions that were studied and the sample in which they were evaluated. Combining methods for addressing internal and external validity can improve the policy relevance of study results. Keywords External validity . Generalizability . Internal validity . Randomized trials . Target population . Transportability
Introduction When identifying the most relevant information for policy makers or clinicians looking to make a decision about how to act in a particular population or for a particular patient, both the actions being considered and the context to which they will be applied matter [1, 2]. One hierarchy of study designs places results from randomized controlled trials (RCTs) at the pinnacle of the pyramid of evidence because RCTs minimize internal bias due to confounding by design through randomization [3]. Setting aside the fact that RCTs may still suffer from internal biases other than confounding bias, RCTs often are conducted in highly selected study samples that may yield This article is part of the Topical Collection on Epidemiologic Methods * Catherine R. Lesko [email protected] 1
Department of Epidemiology, Johns Hopkins School of Public Health, 615 N. Wolfe St., Baltimore, MD 21205, USA
2
Department of Biostatistics, Johns Hopkins School of Public Health, Baltimore, MD, USA
3
Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
a very different context than the target population in which the decision is being made. This mismatch of context in and composition of the trial sample and the target population is a key component of external bias, which is undervalued in this evidence hierarchy. Lest we forget how much the target population matters, we present two examples: (1) estimates of the effect of medication assisted therapy (buprenorphine/naloxone), motivational interviewing, and motivational incentives on substance use would have been very different—typically less effective and no longer statistically significant—had trials testing these interventions bee
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