ArticleAmerican journal of epidemiology2017
Analyses of Sensitivity to the Missing-at-Random Assumption Using Multiple Imputation With Delta Adjustment: Application to a Tuberculosis/HIV Prevalence Survey With Incomplete HIV-Status Data.
Article in American journal of epidemiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.
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Who cites it
47 citing papers in PubMed, 1 synthesis or guideline pooled 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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- Missing not at random in end of life care studies: multiple imputation and sensitivity analysis on data from the ACTION study.BMC medical research methodology · 2021Trial
- Transitions in Co-occurring Problematic Internet Use and Depressive Symptoms Among Adolescents: A Dual-Systems Perspective.Journal of youth and adolescence · 2026Article
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- Childhood maltreatment and joint trajectories of social isolation and depression as predictors of cognitive impairment in late midlife: a prospective cohort study.Epidemiology and psychiatric sciences · 2026Article
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- Beyond mild, moderate, and severe traumatic brain injury: modelling severity from clinical, neuroimaging, and blood-based indicators.EBioMedicine · 2025Article
- Exploring the impact of missing data on maternal tobacco program results: an analysis of self-efficacy on smoking cessation.BMC public health · 2025Article
- Handling Missing Outcome Data in Cluster Randomized Trials With Both Individual- and Cluster-Level Dropout.Statistics in medicine · 2025Article
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- Sensitivity analysis for time-to-event data accounting for intra-individual variability in time-varying covariates with missing data.Scientific reports · 2025Article
- External validation and update of the pediatric asthma risk score as a passive digital marker for childhood asthma using integrated electronic health records.EClinicalMedicine · 2025Article
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4 authors.
Funding
Abstract
Multiple imputation with delta adjustment provides a flexible and transparent means to impute univariate missing data under general missing-not-at-random mechanisms. This facilitates the conduct of analyses assessing sensitivity to the missing-at-random (MAR) assumption. We review the delta-adjustment procedure and demonstrate how it can be used to assess sensitivity to departures from MAR, both when estimating the prevalence of a partially observed outcome and when performing parametric causal mediation analyses with a partially observed mediator. We illustrate the approach using data from 34,446 respondents to a tuberculosis and human immunodeficiency virus (HIV) prevalence survey that was conducted as part of the Zambia-South Africa TB and AIDS Reduction Study (2006-2010). In this study, information on partially observed HIV serological values was supplemented by additional information on self-reported HIV status. We present results from 2 types of sensitivity analysis: The first assumed that the degree of departure from MAR was the same for all individuals with missing HIV serological values; the second assumed that the degree of departure from MAR varied according to an individual's self-reported HIV status. Our analyses demonstrate that multiple imputation offers a principled approach by which to incorporate auxiliary information on self-reported HIV status into analyses based on partially observed HIV serological values.
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