ArticleNature communications2024
Geographic pair matching in large-scale cluster randomized trials.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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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
5 citing papers in PubMed.
- Evaluation of health impacts of a disability-inclusive graduation programme among ultra-poor people with disabilities in Uganda: secondary analysis of a cluster randomized trial.EClinicalMedicine · 2025Article
- Effects of household concrete floors on maternal and child health: the CRADLE trial - a randomised controlled trial protocol.BMJ open · 2025Article
- The use of geographic information systems (GIS) in studying mental health service delivery: A scoping review.Global mental health (Cambridge, England) · 2025Review
- Effects of household concrete floors on maternal and child health - the CRADLE trial: a randomised controlled trial protocol.medRxiv : the preprint server for health sciences · 2024Article
- Geographic pair matching in large-scale cluster randomized trials.Nature communications · 2024Article
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17 authors.
Funding
Abstract
Cluster randomized trials are often used to study large-scale public health interventions. In large trials, even small improvements in statistical efficiency can have profound impacts on the required sample size and cost. Location integrates many socio-demographic and environmental characteristics into a single, readily available feature. Here we show that pair matching by geographic location leads to substantial gains in statistical efficiency for 14 child health outcomes that span growth, development, and infectious disease through a re-analysis of two large-scale trials of nutritional and environmental interventions in Bangladesh and Kenya. Relative efficiencies from pair matching are ≥1.1 for all outcomes and regularly exceed 2.0, meaning an unmatched trial would need to enroll at least twice as many clusters to achieve the same level of precision as the geographically pair matched design. We also show that geographically pair matched designs enable estimation of fine-scale, spatially varying effect heterogeneity under minimal assumptions. Our results demonstrate broad, substantial benefits of geographic pair matching in large-scale, cluster randomized trials.
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