Causal Impact: Epidemiological Approaches for a Public Health of Consequence
Open accessAbstract
Causal Impact: Epidemiological Approaches for a Public Health of Consequence Affiliation Daniel Westreich PhD, Jessie K. Edwards PhD, Elizabeth T. Rogawski PhD, Michael G. Hudgens PhD, Elizabeth A. Stuart PhD, and Stephen R. Cole PhDDaniel Westreich, Jessie K. Edwards, and Stephen R. Cole are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina-Chapel Hill. Elizabeth T. Rogawski is with the Division of Infectious Diseases and International Health, University of Virginia, Charlottesville. Michael G. Hudgens is with the Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina-Chapel Hill. Elizabeth A. Stuart is with the Departments of Biostatistics, Health Policy and Management, and Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.CopyRightCorrespondence should be sent to Daniel Westreich, Associate Professor, Department of Epidemiology, CB 7435 McGavran-Greenberg Hall, Chapel Hill, NC 27599 (e-mail: [email protected]edu). Reprints can be ordered at http://www.ajph.org by clicking the "Reprints" link.CONTRIBUTORSD. Westreich wrote the first draft. All of the authors contributed to the writing and editing of the article. https://doi.org/10.2105/AJPH.2016.303226 Accepted: April 04, 2016 Published Online: May 06, 2016
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
External validity may be threatened by the limited generalizability of study populations to relevant populations or differences between the study environment and real-world interventions.
“External validity may be threatened by the limited generalizability of study populations to relevant populations or differences between the study environment and real-world interventions [18, 19].”
From Causal language and strength of inference in academic and media articles shared in social media (CLAIMS): A systematic review (2018) · cites this paper as [19]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 7 · Cited by 51
- Authors
- Westreich, D., Edwards, J. K., Rogawski, E. T., Hudgens, M. G., Stuart, E. A., & Cole, S. R.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Daniel Westreich, Jessie K. Edwards, and Stephen R. Cole are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina-Chapel Hill. Elizabeth T. Rogawski is with the Division of Infectious Diseases and International Health, University of Virginia, Charlottesville. Michael G. Hudgens is with the Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina-Chapel Hill. Elizabeth A. Stuart is with the Departments of...
- Venue
- American Journal of Public Health
- Publisher
- American Public Health Association
- Published
- 2016-06
- Volume
- 106
- Issue
- 6
- Pages
- 1011-1012
- ISSN
- 0090-0036 (ISSN-L)
- 1541-0048
- PMC
- PMC4880276
- OpenAlex
- W2345363870
- Cited by
- 51
- References
- 7
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 1 · 2023: 2 · 2022: 4 · 2021: 3 · 2020: 7 · 2019: 5 · 2018: 7 · 2017: 13 · 2016: 5
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Public Health (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- Funders
- National Institutes of Health (1dp2hd084070-01)
- Fogarty International Center (D43TW009359)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (DP2-HD-08-4070)
- 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 › Management Science and Operations Research › Evaluation and Performance Assessment
- Keywords
- causal inference, causal effects, public health, epidemiological methods, causal effect estimation
- MeSH terms
- Decision Making, Health Policy, Humans, Public Health, Epidemiologic Studies, Biomedical Research
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review