ArticleInternational journal of epidemiology2020
Common misconceptions about validation studies.
Article in International journal of epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
What it found
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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
35 citing papers in PubMed, 83 citations in OpenAlex.
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- The Rogan-Gladen estimator for outcome misclassification.American journal of epidemiology · 2026Article
- Validation of rule-based detection methods for relapse in multiple sclerosis.BMC medical informatics and decision making · 2026Article
- Long-Term Recall Error in Retrospective Family Surveys: Cohabitation Histories in Denmark.European journal of population = Revue europeenne de demographie · 2026Article
- Adaptive Multi-Wave Sampling for Efficient Chart Validation.Clinical epidemiology · 2026Article
- A systematic review of mathematical and machine learning models of Avian Influenza.One health (Amsterdam, Netherlands) · 2025Review
- Estimating Antigen Test Sensitivity via Target Distribution Balancing: Development and Validation Study.JMIR bioinformatics and biotechnology · 2025Article
- Modern sources of controls in case-control studies.American journal of epidemiology · 2025Article
- Quantifying the primary care workforce in the U.S.: A validation study with and without an imperfectly measured referent standard.Annals of epidemiology · 2025Article
- Predicting progression events in multiple myeloma from routine blood work.NPJ digital medicine · 2025Article
- Validation of Acute Exacerbation of Chronic Obstructive Pulmonary Disease Recording in Electronic Health Records: A Systematic Review.Chronic obstructive pulmonary diseases (Miami, Fla.) · 2025Article
- Parameterization of Beta Distributions for Bias Parameters of Binary Exposure Misclassification in Probabilistic Bias Analysis.Epidemiology (Cambridge, Mass.) · 2025Article
- The use of artificial intelligence in sexual and reproductive health: a comprehensive scoping review.npj women's health · 2025Article
- Validating At-Home Urinary Hormone Measurements in Postpartum and Perimenopause Fertility Transitions.Women's health reports (New Rochelle, N.Y.) · 2025Article
- Guidance of development, validation, and evaluation of algorithms for populating health status in observational studies of routinely collected data (DEVELOP-RCD).Military Medical Research · 2024Article
- Assessing Real-World Data From Electronic Health Records for Health Technology Assessment: The SUITABILITY Checklist: A Good Practices Report of an ISPOR Task Force.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2024Article
- Validity of self-reported night shift work among women with and without breast cancer.Scandinavian journal of work, environment & health · 2024Article
- Validation of human immunodeficiency virus diagnosis codes among women enrollees of a U.S. health plan.BMC health services research · 2024Article
- ADDRESSING SELECTION BIAS AND MEASUREMENT ERROR IN COVID-19 CASE COUNT DATA USING AUXILIARY INFORMATION.The annals of applied statistics · 2023Article
- The effect of disease misclassification on the ability to detect a gene-environment interaction: implications of the specificity of case definitions for research on Gulf War illness.BMC medical research methodology · 2023Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
Information bias is common in epidemiology and can substantially diminish the validity of study results. Validation studies, in which an investigator compares the accuracy of a measure with a gold standard measure, are an important way to understand and mitigate this bias. More attention is being paid to the importance of validation studies in recent years, yet they remain rare in epidemiologic research and, in our experience, they remain poorly understood. Many epidemiologists have not had any experience with validations studies, either in the classroom or in their work. We present an example of misclassification of a dichotomous exposure to elucidate some important misunderstandings about how to conduct validation studies to generate valid information. We demonstrate that careful attention to the design of validation studies is central to determining how the bias parameters (e.g. sensitivity and specificity or positive and negative predictive values) can be used in quantitative bias analyses to appropriately correct for misclassification. Whether sampling is done based on the true gold standard measure, the misclassified measure or at random will determine which parameters are valid and the precision of those estimates. Whether or not the validation is done stratified by other key variables (e.g. by the exposure) will also determine the validity of those estimates. We also present sample questions that can be used to teach these concepts. Increasing the presence of validation studies in the classroom could have a positive impact on their use and improve the validity of estimates of effect in epidemiologic research.
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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.