Cited by 165Advanced Causal Inference TechniquesStatistical Methods in EpidemiologyMeta-analysis and systematic reviews

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Target Validity and the Hierarchy of Study Designs

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Westreich, Daniel, Edwards, Jessie K, Lesko, Catherine R, Cole, Stephen R, Stuart, Elizabeth A·2019·American Journal of Epidemiology

DOI 10.1093/aje/kwy228PMC PMC6357801

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Abstract

In recent years, increasing attention has been paid to problems of external validity, specifically to methodological approaches for both quantitative generalizability and transportability of study results. However, most approaches to these issues have considered external validity separately from internal validity. Here we argue that considering either internal or external validity in isolation may be problematic. Further, we argue that a joint measure of the validity of an effect estimate with respect to a specific population of interest may be more useful: We call this proposed measure target validity. In this work, we introduce and formally define target bias as the total difference between the true causal effect in the target population and the estimated causal effect in the study sample, and target validity as target bias = 0. We illustrate this measure with a series of examples and show how this measure may help us to think more clearly about comparisons between experimental and nonexperimental research results. Specifically, we show that even perfect internal validity does not ensure that a causal effect will be unbiased in a specific target population.

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Untitled work
(2002) · Cited by 13,211
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Air Pollution and Hospital Admissions for Heart Disease in Eight U.S. Counties
Schwartz, J. D. (1999) · Epidemiology · doi:10.1097/00001648-199901000-00005 · Cited by 3,045
Understanding and misunderstanding randomized controlled trials
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Maternal Pesticide Exposure from Multiple Sources and Selected Congenital Anomalies
Shaw, G. M., Wasserman, C. R., O’Malley, C. D., Nelson, V. E., & Jackson, R. J. (1999) · Epidemiology · doi:10.1097/00001648-199901000-00011 · Cited by 1,783
8. Misunderstandings Between Experimentalists and Observationalists About Causal Inference
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Self-citation
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The Ethics of Childhood Obesity Treatment - from the Childhood Obesity Task Force (COTF) of European Association for the Study of Obesity (EASO)
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Self-citation

Show all 34 references

Research works printed but not linked: 4

Bareinboim, 2014, Advances in Neural Information Processing Systems 26., 136
Bareinboim, 2015, Advances in Neural Information Processing Systems 27., 280
Pearl, 2011, 2011 JSM Proceedings: Papers Presented at the Joint Statistical Meetings, Miami Beach, Florida, July 30–August 4, 2011, and Other ASA-Sponsored Conferences, 157
Bareinboim, 2014, Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence and the Twenty-Sixth Innovative Applications of Artificial Intelligence Conference., 2410

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Authors: Westreich, D., Edwards, J. K., Lesko, C. R., Cole, S. R., & Stuart, E. A.
Affiliations: University of North Carolina at Chapel Hill (US)
Johns Hopkins University (US)
Corresponding author: Westreich, Daniel
ORCID: Westreich, Daniel
Edwards, Jessie K
Lesko, Catherine R
Cole, Stephen R
Stuart, Elizabeth A
Venue: American Journal of Epidemiology
Publisher: Oxford University Press (OUP)
Published: 2018-10-09
Volume: 188
Issue: 2
Pages: 438-443
ISSN: 0002-9262 (ISSN-L)
1476-6256
DOI: 10.1093/aje/kwy228
PMC: PMC6357801
OpenAlex: W2900846215
Cited by: 165
References: 34
Citations by year: 2026: 15 · 2025: 15 · 2024: 28 · 2023: 26 · 2022: 24 · 2021: 21 · 2020: 23 · 2019: 12
FWCI: 11.62
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
Locations: American Journal of Epidemiology (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
UNC Libraries
Funders: Eunice Kennedy Shriver National Institute of Child Health and Human Development
National Institutes of Health (DP2-HD084070)
National Institute of Allergy and Infectious Diseases (R01 AI100654)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Keywords: target bias, generalizability, internal validity, causal effect estimation, target population, transportability, causal inference
MeSH terms: Epidemiologic Methods, Humans, Reproducibility of Results, Bias, Causality

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