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[Preprint]. 2023 May 23:2023.04.30.23289317.

doi: 10.1101/2023.04.30.23289317.

Geographic pair-matching in large-scale cluster randomized trials

Benjamin F Arnold^{1

2}, Francois Rerolle¹, Christine Tedijanto¹, Sammy M Njenga³, Mahbubur Rahman⁴, Ayse Ercumen⁵, Andrew Mertens⁶, Amy Pickering^{7

8}, Audrie Lin⁹, Charles D Arnold¹⁰, Kishor Das¹¹, Christine P Stewart¹⁰, Clair Null¹², Stephen P Luby¹³, John M Colford Jr⁶, Alan E Hubbard¹⁴, Jade Benjamin-Chung^{8

15}

Affiliations

¹ Francis I. Proctor Foundation, University of California, San Francisco, CA, USA.
² Department of Ophthalmology, University of California, San Francisco, CA, USA.
³ Eastern and Southern Africa Centre of International Parasite Control, Kenya Medical Research Institute, Nairobi, Kenya.
⁴ Environmental Interventions Unit, Infectious Diseases Division, icddr,b, Dhaka, Bangladesh.
⁵ Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, USA.
⁶ Division of Epidemiology, School of Public Health, University of California, Berkeley, CA, USA.
⁷ Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA.
⁸ Chan Zuckerberg Biohub, San Francisco, CA.
⁹ Department of Biobehavioral Health, Pennsylvania State University, University Park, PA, USA.
¹⁰ Department of Nutrition, University of California, Davis, CA.
¹¹ School of Mathematical and Statistical Sciences, University of Galway, Galway, Ireland.
¹² Mathematica, Washington, DC, USA.
¹³ Infectious diseases and Geographic Medicine, Stanford University, Stanford, California.
¹⁴ Division of Biostatistics, School of Public Health, University of California, Berkeley, CA, USA.
¹⁵ Department of Epidemiology and Population Health, Stanford University, CA, USA.

PMID: 37205361
PMCID: PMC10187339
DOI: 10.1101/2023.04.30.23289317

Geographic pair-matching in large-scale cluster randomized trials

Benjamin F Arnold et al. medRxiv. 2023.

[Preprint]. 2023 May 23:2023.04.30.23289317.

doi: 10.1101/2023.04.30.23289317.

Authors

Affiliations

¹ Francis I. Proctor Foundation, University of California, San Francisco, CA, USA.
² Department of Ophthalmology, University of California, San Francisco, CA, USA.
³ Eastern and Southern Africa Centre of International Parasite Control, Kenya Medical Research Institute, Nairobi, Kenya.
⁴ Environmental Interventions Unit, Infectious Diseases Division, icddr,b, Dhaka, Bangladesh.
⁵ Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, USA.
⁶ Division of Epidemiology, School of Public Health, University of California, Berkeley, CA, USA.
⁷ Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA.
⁸ Chan Zuckerberg Biohub, San Francisco, CA.
⁹ Department of Biobehavioral Health, Pennsylvania State University, University Park, PA, USA.
¹⁰ Department of Nutrition, University of California, Davis, CA.
¹¹ School of Mathematical and Statistical Sciences, University of Galway, Galway, Ireland.
¹² Mathematica, Washington, DC, USA.
¹³ Infectious diseases and Geographic Medicine, Stanford University, Stanford, California.
¹⁴ Division of Biostatistics, School of Public Health, University of California, Berkeley, CA, USA.
¹⁵ Department of Epidemiology and Population Health, Stanford University, CA, USA.

PMID: 37205361
PMCID: PMC10187339
DOI: 10.1101/2023.04.30.23289317

Update in

Geographic pair matching in large-scale cluster randomized trials.
Arnold BF, Rerolle F, Tedijanto C, Njenga SM, Rahman M, Ercumen A, Mertens A, Pickering AJ, Lin A, Arnold CD, Das K, Stewart CP, Null C, Luby SP, Colford JM Jr, Hubbard AE, Benjamin-Chung J. Arnold BF, et al. Nat Commun. 2024 Feb 5;15(1):1069. doi: 10.1038/s41467-024-45152-y. Nat Commun. 2024. PMID: 38316755 Free PMC article.

Abstract

Custer 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. Pair matched randomization is one strategy with potential to increase trial efficiency, but to our knowledge there have been no empirical evaluations of pair-matching in large-scale, epidemiologic field trials. Location integrates many socio-demographic and environmental characteristics into a single feature. Here, we show that geographic pair-matching 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. We estimate relative efficiencies ≥1.1 for all outcomes assessed and relative efficiencies regularly exceed 2.0, meaning an unmatched trial would have needed 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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Conflict of interest statement

Competing interests The authors declare no competing interests.

References

1. Murray D. M., Varnell S. P. & Blitstein J. L. Design and analysis of group-randomized trials: a review of recent methodological developments. Am J Public Health 94, 423–432 (2004). - PMC - PubMed
1. Dron L. et al. The role and challenges of cluster randomised trials for global health. Lancet Glob. Health 9, e701–e710 (2021). - PubMed
1. Hayes R. J. & Moulton L. H. Cluster randomised trials. (Taylor & Francis Group, 2017).
1. Luby S. P. et al. Effects of water quality, sanitation, handwashing, and nutritional interventions on diarrhoea and child growth in rural Bangladesh: a cluster randomised controlled trial. Lancet Glob Health 6, e302–e315 (2018). - PMC - PubMed
1. Null C. et al. Effects of water quality, sanitation, handwashing, and nutritional interventions on diarrhoea and child growth in rural Kenya: a cluster-randomised controlled trial. Lancet Glob Health 6, e316–e329 (2018). - PMC - PubMed

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This is a preprint.

Geographic pair-matching in large-scale cluster randomized trials

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Geographic pair-matching in large-scale cluster randomized trials

Authors

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Update in

Abstract

Conflict of interest statement

References

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