ArticleInternational journal of statistics in medical research
Multiple Imputation by Fully Conditional Specification for Dealing with Missing Data in a Large Epidemiologic Study.
Article in International journal of statistics in medical research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 253 papers, 5 of them syntheses that pooled it.
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Who cites it
253 citing papers in PubMed, 5 syntheses or guidelines pooled it.
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- The association between diabetes and gastric cancer: results from the Stomach Cancer Pooling Project Consortium.European journal of cancer prevention : the official journal of the European Cancer Prevention Organisation (ECP) · 2022Pooled it
- Analytical methods used in estimating the prevalence of HIV/AIDS from demographic and cross-sectional surveys with missing data: a systematic review.BMC medical research methodology · 2020Pooled it
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- Obesity at age 20 and weight gain during adulthood increase risk of total and premature all-cause mortality: findings from women attending breast screening in Manchester.BMC women's health · 2023Trial
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- Understanding higher substance use among early adolescent females: A decomposition analysis of adverse childhood experiences, bullying victimization, and depressive symptoms.Addictive behaviors reports · 2026Article
- Discrimination and risk of spontaneous abortion in a preconception cohort study.Social science & medicine (1982) · 2026Article
- Unlocking the Power of Neighborhood Collective Efficacy: Associations with ADHD and Youth Outcomes Among Black and White Adolescents.Journal of racial and ethnic health disparities · 2026Article
- Per- and Polyfluoroalkyl Substances (PFAS) Exposure Profiles and Their Predictors in a Study of US Volunteer Firefighters.American journal of industrial medicine · 2026Article
- Enhancing Care for Critically Ill Patients Boarding in the Emergency Department: A 360° Evaluation of an Emergency Medicine Critical Care Fellow Model.Journal of the American College of Emergency Physicians open · 2026Article
- Sex Differences in Cancer Stage at Diagnosis of Nonreproductive Solid Organ Tumors in the United States, 2015 to 2022.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026Article
193 more citing papers are in PubMed but not listed here.
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Authors and funding
2 authors.
Funding
Abstract
Missing data commonly occur in large epidemiologic studies. Ignoring incompleteness or handling the data inappropriately may bias study results, reduce power and efficiency, and alter important risk/benefit relationships. Standard ways of dealing with missing values, such as complete case analysis (CCA), are generally inappropriate due to the loss of precision and risk of bias. Multiple imputation by fully conditional specification (FCS MI) is a powerful and statistically valid method for creating imputations in large data sets which include both categorical and continuous variables. It specifies the multivariate imputation model on a variable-by-variable basis and offers a principled yet flexible method of addressing missing data, which is particularly useful for large data sets with complex data structures. However, FCS MI is still rarely used in epidemiology, and few practical resources exist to guide researchers in the implementation of this technique. We demonstrate the application of FCS MI in support of a large epidemiologic study evaluating national blood utilization patterns in a sub-Saharan African country. A number of practical tips and guidelines for implementing FCS MI based on this experience are described.
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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.