ArticleAmerican journal of epidemiology2018
Principled Approaches to Missing Data in Epidemiologic Studies.
Article in American journal of epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 126 papers, 4 of them syntheses that pooled it.
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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
126 citing papers in PubMed, 4 syntheses or guidelines pooled it, 242 citations in OpenAlex.
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- Prophylactic anticoagulation with low molecular weight heparin in COVID-19: cohort studies in Denmark and Sweden.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2022Pooled it
- A systematic review of how missing data are handled and reported in multi-database pharmacoepidemiologic studies.Pharmacoepidemiology and drug safety · 2021Pooled it
- The progression rate of peripheral arterial disease in patients with intermittent claudication: a systematic review.Journal of foot and ankle research · 2019Pooled it
- Reduction of cardiovascular risk factors among young men with hypertension using an interactive decision aid: cluster-randomized control trial.BMC cardiovascular disorders · 2021Trial
- Far from MCAR: Obtaining Population-level Estimates of HIV Viral Suppression.Epidemiology (Cambridge, Mass.) · 2020Trial
- Flow Cytometric Lymphocyte Subset Enumeration for Lymphopenia Grading and C-Reactive Protein-Defined Inflammation Discrimination.Journal of clinical laboratory analysis · 2026Article
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- Maternal Adverse Childhood Experiences, Postpartum Care Utilisation, and Postpartum Depressive Symptoms.Paediatric and perinatal epidemiology · 2026Article
- Exploring self-referral as a low-burden, universally administered strategy to connect adolescents to mental health supports following anonymous school-based screening.School psychology (Washington, D.C.) · 2026Article
- A powerful representation learning method for enhanced analysis of incomplete multi-omics data.NPJ systems biology and applications · 2026Article
- Pregnancy identification method as a source of bias in studies of prenatal exposures using real-world data.American journal of epidemiology · 2026Article
- Statistical Accuracy of Administratively Recorded Race/Ethnicity in the Military Health System and Race/Ethnicity Ascertained via Questionnaire.Journal of racial and ethnic health disparities · 2026Article
- Adjusting for selection bias due to missing eligibility criteria in emulated target trials.American journal of epidemiology · 2025Article
- Comparing causal inference methods for point exposures with missing confounders: a simulation study.BMC medical research methodology · 2025Article
- Article
- Recommendations for a Complete Reporting of Statistical Methods in Veterinary Pharmacology.Journal of veterinary pharmacology and therapeutics · 2025Review
- Pitfalls of imputing using incomplete auxiliary variables.American journal of epidemiology · 2025Article
- Maternal Cardiometabolic Risk Factors in Pregnancy and Offspring Blood Pressure at Age 2 to 18 Years.JAMA network open · 2025Article
66 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors at 5 institutions in 1 country.
Funding
Abstract
Principled methods with which to appropriately analyze missing data have long existed; however, broad implementation of these methods remains challenging. In this and 2 companion papers (Am J Epidemiol. 2018;187(3):576-584 and Am J Epidemiol. 2018;187(3):585-591), we discuss issues pertaining to missing data in the epidemiologic literature. We provide details regarding missing-data mechanisms and nomenclature and encourage the conduct of principled analyses through a detailed comparison of multiple imputation and inverse probability weighting. Data from the Collaborative Perinatal Project, a multisite US study conducted from 1959 to 1974, are used to create a masked data-analytical challenge with missing data induced by known mechanisms. We illustrate the deleterious effects of missing data with naive methods and show how principled methods can sometimes mitigate such effects. For example, when data were missing at random, naive methods showed a spurious protective effect of smoking on the risk of spontaneous abortion (odds ratio (OR) = 0.43, 95% confidence interval (CI): 0.19, 0.93), while implementation of principled methods multiple imputation (OR = 1.30, 95% CI: 0.95, 1.77) or augmented inverse probability weighting (OR = 1.40, 95% CI: 1.00, 1.97) provided estimates closer to the "true" full-data effect (OR = 1.31, 95% CI: 1.05, 1.64). We call for greater acknowledgement of and attention to missing data and for the broad use of principled missing-data methods in epidemiologic research.
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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.