Evidence map›Paper›PMID 40680786›Full record

ArticleStatistics in medicine2025

Exposure Measurement Error Correction in Longitudinal Studies With Discrete Outcomes.

Ce Yang, Ning Zhang, Jiaxuan Li, Unnati V Mehta, Jaime E Hart, Donna L Spiegelman, Molin Wang

Abstract read
In one paragraph

Article in Statistics in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Ce YangDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-2830-6672
Ning ZhangDepartment of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA.ORCID https://orcid.org/0000-0001-6590-2484
Jiaxuan LiDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Unnati V MehtaDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Jaime E HartDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Donna L SpiegelmanDepartment of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USA.
Molin WangDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0003-1951-8961

Funding

Translational Research Support CoreP30ES000002 · NIEHS · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI JAIME ELIZABETH HART · 1985 to 2026
$44.6M
Life Course Cancer Epidemiology Cohort in WomenU01CA176726 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI ELIASSEN, A. HEATHER, WILLETT, WALTER C. · 2018 to 2025
$22.4M
Statistical Methods to Account for Exposure Uncertainty in Environmental EpidemiologyR01ES026246 · NIEHS · YALE UNIVERSITY · PI SPIEGELMAN, DONNA L · 2018 to 2022
$3.1M
New Epidemiologic Methods for Reducing Measurement Error and Misclassification Bias in Cancer EpidemiologyR01CA279175 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI SPIEGELMAN, DONNA L, WANG, MOLIN · 2023 to 2025
$2.8M
What Causes Hearing Loss: Advancing the MethodsR01DC017717 · NIDCD · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Molin Wang · 2019 to 2026
$2.6M
NCI NIH HHS R01 CA279175NCI NIH HHS U01 CA176726NIDCD NIH HHS R01 DC017717NIEHS NIH HHS 5R01ES026246NIEHS NIH HHS P30 ES000002NIEHS NIH HHS R01 ES026246NIH HHS R01CA279175NIH HHS R01 DC017717NIH HHS U01CA176726
6 · The paper itself

Abstract

Environmental epidemiologists are often interested in estimating the effect of time-varying functions of the exposure history on health outcomes. However, the individual exposure measurements that constitute the history upon which an exposure history function is constructed are usually subject to measurement errors. To obtain unbiased estimates of the effects of such mismeasured functions in longitudinal studies with discrete outcomes, a method applicable to the main study/validation study design is developed. Various estimation procedures are explored. Simulation studies were conducted to assess its performance compared to standard analysis, and we found that the proposed method had good performance in terms of finite sample bias reduction and nominal coverage probability improvement. As an illustrative example, we applied the new method to a study of long-term exposure to

Indexed as

Environmental ExposureAnxiety DisordersBiasComputer SimulationHumansLongitudinal StudiesModels, StatisticalParticulate MatterParticulate Matterair pollutionanxietygeneralized estimating equationlongitudinal datameasurement error correction

Identifiers

PMID40680786
PMCPMC12274082

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.