The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Invited Commentary: Ecologic Studies—Biases, Misconceptions, and Counterexamples
Abstract
Many authors have pointed out that relative-risk estimates derived from ecologic data are vulnerable to biases not found in estimates derived from individual-level data. Nevertheless, biases in ecologic studies still are often dealt with in the same manner as biases in other observational studies, and so are not given adequate treatment. This commentary reviews and illustrates some of the more recent findings about bias in ecologic estimates. Special attention is given to problems of ecologic confounder control when individual risks follow a nonlinear model, and to misconceptions about ecologic bias that have appeared in the literature.
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“In aggregate outcome data, it cannot be known that the individual experiencing the exposure is the same individual within the group that had an autism diagnosis. Furthermore, it is not possible to account for individual-level confounding influences in this type of design”
From Environmental Chemical Exposures and Autism Spectrum Disorders: A Review of the Epidemiological Evidence (2014) · cites this paper as [17]
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Metadata
- Authors
- Greenland, S., & Robins, J.
- Affiliations
- University of California, Los Angeles (US)
- Harvard University (US)
- Corresponding author
- Greenland, Sander
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 1994-04-15
- Volume
- 139
- Issue
- 8
- Pages
- 747-760
- ISSN
- 0002-9262 (ISSN-L)
- 1476-6256
- OpenAlex
- W2131305454
- Cited by
- 494
- References
- 21
- Citations by year
- 2026: 22 · 2025: 7 · 2024: 8 · 2023: 10 · 2022: 10 · 2021: 19 · 2020: 14 · 2019: 6 · 2018: 7 · 2017: 8 · 2016: 15 · 2015: 15 · 2014: 19 · 2013: 16 · 2012: 11
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5k04es000180-03)
- National Institute of Allergy and Infectious Diseases (R01AI032475)
- National Institute of Environmental Health Sciences (P30ES000002, K04-ES00180)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- ecological study, relative risk estimation, confounder control, microdata, bias in observational studies
- MeSH terms
- Ecology, Epidemiologic Methods, Humans, Regression Analysis, Risk, Models, Statistical, Bias, Confounding Factors, Epidemiologic
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 ›
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