ArticleStatistical methods in medical research2021
Adjusting for selection bias due to missing data in electronic health records-based research.
Article in Statistical methods in medical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Missing data handling in pediatric appendectomy research: current practices and National Surgical Quality Improvement Program (NSQIP) analysis.Surgical endoscopy · 2026Pooled it
- Exploring quality of life and physical-physiological characteristics in obese patients with and without lipedema: insights from the LipObes study.BMC women's health · 2026Article
- How representative are electronic health records? A record linkage study using individual-level census data.Social science & medicine (1982) · 2026Article
- Baseline Blood Eosinophil Count and 28-Day in-Hospital Mortality in ICU-Admitted Patients with AECOPD: A Cohort Study with External Validation.International journal of chronic obstructive pulmonary disease · 2026Article
- Using metabolic syndrome severity in the "real world": Associations with diabetes and cardiovascular disease in all of us vs. NHANES.Metabolism open · 2025Article
- Overcoming data challenges through enriched validation and targeted sampling to measure whole-person health in electronic health records.Journal of biomedical informatics · 2025Article
- Demystifying Clone-Censor-Weighting to Studying Treatment Initiation Windows: An Example Using Publicly Available Synthetic Medicare Claims Data.Pharmacoepidemiology and drug safety · 2025Article
- Adjusting for Selection Bias Due to Missing Data in Electronic Health Records-Based Research by Blending Multiple Imputation and Inverse Probability Weighting.Statistics in medicine · 2025Article
- Robust causal inference for point exposures with missing confounders.The Canadian journal of statistics = Revue canadienne de statistique · 2025Article
- Estimating weighted quantile treatment effects with missing outcome data by double sampling.Biometrics · 2025Article
- Exposure to autoimmune disorders is associated with increased Alzheimer's disease risk in a multi-site electronic health record analysis.Cell reports. Medicine · 2025Observational
- An open-source framework for end-to-end analysis of electronic health record data.Nature medicine · 2024Article
- Addressing Information Biases Within Electronic Health Record Data to Improve the Examination of Epidemiologic Associations With Diabetes Prevalence Among Young Adults: Cross-Sectional Study.JMIR medical informatics · 2024Article
- Addressing label noise for electronic health records: insights from computer vision for tabular data.BMC medical informatics and decision making · 2024Article
- To weight or not to weight? The effect of selection bias in 3 large electronic health record-linked biobanks and recommendations for practice.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Biases in Electronic Health Records Data for Generating Real-World Evidence: An Overview.Journal of healthcare informatics research · 2024Article
- To weight or not to weight? Studying the effect of selection bias in three large EHR-linked biobanks.medRxiv : the preprint server for health sciences · 2024Article
- Prepregnancy obesity and risk of placental inflammation at term: a selection bias analysis.Annals of epidemiology · 2023Article
- Social inequalities and long-term health impact of COVID-19 in Belgium: protocol of the HELICON population data linkage.BMJ open · 2023Article
- Data Provenance in Biomedical Research: Scoping Review.Journal of medical Internet research · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
While electronic health records data provide unique opportunities for research, numerous methodological issues must be considered. Among these, selection bias due to incomplete/missing data has received far less attention than other issues. Unfortunately, standard missing data approaches (e.g. inverse-probability weighting and multiple imputation) generally fail to acknowledge the complex interplay of heterogeneous decisions made by patients, providers, and health systems that govern whether specific data elements in the electronic health records are observed. This, in turn, renders the missing-at-random assumption difficult to believe in standard approaches. In the clinical literature, the collection of decisions that gives rise to the observed data is referred to as the
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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.