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Cited by 292

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Reproducible Epidemiologic Research

Peng, Roger D., Dominici, Francesca, Zeger, Scott L.·2006·American Journal of Epidemiology

Abstract

The replication of important findings by multiple independent investigators is fundamental to the accumulation of scientific evidence. Researchers in the biologic and physical sciences expect results to be replicated by independent data, analytical methods, laboratories, and instruments. Epidemiologic studies are commonly used to quantify small health effects of important, but subtle, risk factors, and replication is of critical importance where results can inform substantial policy decisions. However, because of the time, expense, and opportunism of many current epidemiologic studies, it is often impossible to fully replicate their findings. An attainable minimum standard is "reproducibility," which calls for data sets and software to be made available for verifying published findings and conducting alternative analyses. The authors outline a standard for reproducibility and evaluate the reproducibility of current epidemiologic research. They also propose methods for reproducible research and implement them by use of a case study in air pollution and health.

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Registry

Crossref · 10.1093/aje/kwj093

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Metadata

Authors
Peng, R. D., Dominici, F., & Zeger, S. L.
Venue
American Journal of Epidemiology
Published
2006-03-01
Volume
163
Issue
9
Pages
783-789
ISSN
  • 0002-9262 (ISSN-L)
  • 1476-6256
OpenAlex
W2169512394
Cited by
292
References
3
FWCI
36.90
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Reproducible Epidemiologic Research. https://app.cochat.ai/papers/10.1093/aje/kwj093
The paper
Peng, R. D., Dominici, F., & Zeger, S. L. (2006). Reproducible Epidemiologic Research. American Journal of Epidemiology. https://doi.org/10.1093/aje/kwj093

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.