ReviewAnnals of epidemiology2018
Epidemiologic analyses with error-prone exposures: review of current practice and recommendations.
Review in Annals of epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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.
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.
Who cites it
51 citing papers in PubMed.
- Food frequency questionnaires are ranking tools, not rulers: a measurement problem hiding in plain sight.European journal of clinical nutrition · 2026Review
- Advancing Long-Term Outdoor Air Pollution Exposure Assessment for Health Studies: Lessons from a Multinational Research Initiative.Current environmental health reports · 2026Review
- The silent normalization of biological exposures in operating rooms: an overlooked occupational crisis.Patient safety in surgery · 2026Article
- Potential Exposure Characteristics and Self-Reported Symptom Burden in a Romanian Region with Heterogeneous Arsenic-Related Drinking-Water Risk.Journal of xenobiotics · 2026Article
- Total Sugars Misreporting in Self-Reported 24-Hour Recalls in the Study of Latinos: Nutrition and Physical Activity Assessment Study.The Journal of nutrition · 2026Article
- Article
- How can the use of different modes of survey data collection introduce bias? An introduction to mode effects using directed acyclic graphs (DAGs).American journal of epidemiology · 2026Article
- Article
- Standardized Methods for Evaluating Physical and Eating Behaviors: The WEALTH Cross-Sectional Study Protocol.JMIR research protocols · 2026Article
- Spatial Patterns of Breast Cancer Risk Associated with Industrial and Environmental Pollutants: A Scoping Review.Toxics · 2026Review
- Improving transportability of regression calibration under the main/external validation study design.Biometrics · 2026Article
- Exposure measurement error in air-pollution epidemiology and its determinants: results from the MELONS study.International journal of epidemiology · 2026Article
- Non-nutritive sweeteners and body weight in children with type 1 and type 2 diabetes: a critical narrative review of current evidence, methodological challenges, biological mechanisms, and clinical implications.Frontiers in nutrition · 2026Review
- Article
- Polygenic risk score and cluster-based analysis suggests links between type 2 diabetes and vascular dementia in the KARE study.Nature communications · 2025Article
- Quality improvement project to transition psychosocial oncology clinical care to a telehealth workflow during the COVID-19 pandemic: a quasi-experimental study.BMC health services research · 2025Article
- Simulated Impact of Vitamin A-Fortified Sugar on Dietary Adequacy and Association of Usual Sugar Intake With Plasma and Breast Milk Retinol Among Lactating Zambian Women.Maternal & child nutrition · 2025Article
- Quantitative bias analysis for mismeasured variables in health research: a review of software tools.BMC medical research methodology · 2025Review
- Article
- Data-driven simulations to assess the impact of study imperfections in time-to-event analyses.American journal of epidemiology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
purposeVariables in observational studies are commonly subject to measurement error, but the impact of such errors is frequently ignored. As part of the STRengthening Analytical Thinking for Observational Studies Initiative, a task group on measurement error and misclassification seeks to describe the current practice for acknowledging and addressing measurement error.
methodsTask group on measurement error and misclassification conducted a literature survey of four types of research studies that are typically impacted by exposure measurement error: (1) dietary intake cohort studies, (2) dietary intake population surveys, (3) physical activity cohort studies, and (4) air pollution cohort studies.
resultsThe survey revealed that while researchers were generally aware that measurement error affected their studies, very few adjusted their analysis for the error. Most articles provided incomplete discussion of the potential effects of measurement error on their results. Regression calibration was the most widely used method of adjustment.
conclusionsMethods to correct for measurement error are available but require additional data regarding the error structure. There is a great need to incorporate such data collection within study designs and improve the analytical approach. Increased efforts by investigators, editors, and reviewers are needed to improve presentation of research when data are subject to error.
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What OpenQuestion holds
Registered trials
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.