ArticleBMC medical research methodology2019
Heckman-type selection models to obtain unbiased estimates with missing measures outcome: theoretical considerations and an application to missing birth weight data.
Article in BMC medical research methodology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
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- Birth Weight Measurement Gaps and Global Kidney Health.Kidney360 · 2026Article
- Variation in stroke survivors' long-term home care use: a South London population-based study.European stroke journal · 2026Article
- Inequities in Neuropsychiatric Outcomes After Brain Trauma in the All of Us Database.JAMA network open · 2025Article
- Bridging urban-rural disparities in malaria care during pregnancy in Senegal: evidence from household and health facility surveys.Infectious diseases of poverty · 2025Article
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- Using an Interactive Voice Response Survey to Assess Patient Satisfaction in Ethiopia: Development and Feasibility Study.JMIR formative research · 2025Article
- Using instruments for selection to adjust for selection bias in Mendelian randomization.Statistics in medicine · 2024Article
- Multilevel Determinants of Long COVID and Potential for Telehealth Intervention.Ethnicity & disease · 2024Article
- Analyzing the determinants of beef cattle commercialization and Its market inefficiency: A case study of Pabna district, Bangladesh.PloS one · 2024Article
- Factor associated with willingness to pay for prevention of cancer: a study of prostate cancer screening.Cost effectiveness and resource allocation : C/E · 2023Article
- Breastfeeding is associated with the intelligence of school-age children in Mexico.Maternal & child nutrition · 2023Article
- Epidemiology of type 2 diabetes mellitus and treatment utilization patterns among the elderly from the first wave of Longitudinal Aging study in India (2017-18)using a Heckman selection model.BMC public health · 2023Article
- Happiness in Old Age: The Daughter Connection.Journal of happiness studies · 2023Article
- Modelling hospital outcome: problems with endogeneity.BMC medical research methodology · 2021Article
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5 authors.
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Abstract
backgroundIn low-income settings, key outcomes such as biomarkers or clinical assessments are often missing for a substantial proportion of the study population. The aim of this study was to assess the extent to which Heckman-type selection models can create unbiased estimates in such settings.
methodsWe introduce the basic Heckman model in a first stage, and then use simulation models to compare the performance of the model to alternative approaches used in the literature for missing outcome data, including complete case analysis (CCA), multiple imputations by chained equations (MICE) and pattern imputation with delta adjustment (PIDA). Last, we use a large population-representative data set on antenatal supplementation (AS) and birth outcomes from Côte d'Ivoire to illustrate the empirical relevance of this method.
resultsAll models performed well when data were missing at random. When missingness in the outcome data was related to unobserved determinants of the outcome, large and systematic biases were found for CCA and MICE, while Heckman-style selection models yielded unbiased estimates. Using Heckman-type selection models to correct for missingness in our empirical application, we found supplementation effect sizes that were very close to those reported in the most recent systematic review of clinical AS trials.
conclusionMissingness in health outcome can lead to substantial bias. Heckman-selection models can correct for this selection bias and yield unbiased estimates, even when the proportion of missing data is substantial.
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