ArticleStatistical methods in medical research2021
Multiple imputation with missing data indicators.
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 63 papers.
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Who cites it
63 citing papers in PubMed.
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- Association between chronic bronchitis and increased breast cancer risk in female patients.Public health action · 2026Article
- Estimated plasma volume for predicting sepsis-associated ARDS risk: a multicentre retrospective cohort study.BMJ open respiratory research · 2026Article
- Enhancing propensity score analysis with data missing not at random: Introducing dual-forest proximity imputation.Behavior research methods · 2026Article
- A metabolic-inflammatory phenotype of pelvic floor dysfunction: A machine learning-based cross-sectional study in a nationally representative US population.The Journal of international medical research · 2026Article
- Longitudinal associations between fast food outlet count and inflammatory markers in the US-based nurses' health study II between 1998 and 2011.Nutrition, metabolism, and cardiovascular diseases : NMCD · 2026Article
- Racial and ethnic disparities in environmental chemical exposures and hypertensive disorders of pregnancy: The ECHO-wide cohort study.Environmental pollution (Barking, Essex : 1987) · 2026Article
- Development of a machine learning-based model for predicting postoperative survival in gastric cancer.World journal of gastrointestinal surgery · 2026Article
- Sex differences in the association of vascular risk and APOE Genotype with cognitive decline and dementia: evidence from a U.S. longitudinal study.Lancet regional health. Americas · 2026Article
- Efficacy and safety of MuShengshu in the treatment of mild-to-moderate atopic dermatitis: protocol for a randomized, double-blind, placebo-controlled trial.Frontiers in medicine · 2026Article
- Development and validation of machine learning for pathological changes in high myopia patients with tessellated fundus: a cross-sectional study.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026Article
- Associations between triglyceride-glucose-derived indices combined with the atherogenic index of plasma and the precise severity of newly diagnosed coronary artery disease: a quantile regressions analysis.Frontiers in nutrition · 2026Article
- [Inflammatory phenotypes in sepsis and the role of vitamin C on the corresponding phenotypes].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025Article
- Prognostic nutritional index is a predictor of adverse outcomes in hospitalized COVID-19 patients: a single-center, retrospective cohort study.BMC infectious diseases · 2025Article
- Psychological and Demographic Predictors of Insomnia Severity: Evidence from a Community Sample in Ecuador.Behavioral sciences (Basel, Switzerland) · 2025Article
- Predictors affecting initial assessment results using driving simulator in stroke patients admitted at a subacute rehabilitation hospital.The British journal of occupational therapy · 2025Article
- Marital Failure and Subsequent Heart Failure: A Prospective Study.Journal of the American Heart Association · 2025Article
- The association between all-cause mortality with drinking habits and water sources: a nationwide longitudinal study on Chinese elderly.Journal of global health · 2025Article
- HOME protocol for a national online survey of people who inject drugs.Harm reduction journal · 2025Article
- A novel nomogram for predicting prolonged disorders of consciousness in severe supratentorial hypertensive intracerebral hemorrhage patients.Scientific reports · 2025Article
3 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
Multiple imputation is a well-established general technique for analyzing data with missing values. A convenient way to implement multiple imputation is sequential regression multiple imputation, also called chained equations multiple imputation. In this approach, we impute missing values using regression models for each variable, conditional on the other variables in the data. This approach, however, assumes that the missingness mechanism is missing at random, and it is not well-justified under not-at-random missingness without additional modification. In this paper, we describe how we can generalize the sequential regression multiple imputation imputation procedure to handle missingness not at random in the setting where missingness may depend on other variables that are also missing but not on the missing variable itself, conditioning on fully observed variables. We provide algebraic justification for several generalizations of standard sequential regression multiple imputation using Taylor series and other approximations of the target imputation distribution under missingness not at random. Resulting regression model approximations include indicators for missingness, interactions, or other functions of the missingness not at random missingness model and observed data. In a simulation study, we demonstrate that the proposed sequential regression multiple imputation modifications result in reduced bias in the final analysis compared to standard sequential regression multiple imputation, with an approximation strategy involving inclusion of an offset in the imputation model performing the best overall. The method is illustrated in a breast cancer study, where the goal is to estimate the prevalence of a specific genetic pathogenic variant.
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Registered trials
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