A Second Chance to Get Causal Inference Right: A Classification of Data Science Tasks
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For much of the recent history of science, learning from data was the academic realm of statistics,1,2 but in the early 20th century, the founders of modern statistics made a momentous decision abo...
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ML can play a role in causal inference, including in policy problems and in climate-relevant scenarios such as estimating the effects of temperature on human mortality and the effects of World Bank projects on vegetative cover.
“ML can play a role in causal inference [41,340,619], including in the context of policy problems [40,453] and in climate-relevant scenarios such as estimating the effects of temperature on human mortality [356] and the effects of World Bank projects on vegetative cover [883].”
From Tackling climate change with machine learning (2023) · cites this paper as [340]
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Shearer, J. E., Jones, R. L., Parker, R., Ferguson, J., & Rowe, I. A. C. (2022) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2022.03.015 · Cited by 33 · see citing works
Leborgne, F., Chatton, A., Léger, M., Lenain, R., & Foucher, Y. (2021) · Scientific Reports · doi:10.1038/s41598-021-81110-0 · Cited by 26 · see citing works
Movement Difficulties at Age Five Among Extremely Preterm Infants
Aubert, A. M., Costa, R. A., Ådén, U., Cuttini, M., Männamaa, M., Pierrat, V., Sarrechia, I., van Heijst, A. F. J., Zemlin, M., Johnson, S. J., et al. (2022) · PEDIATRICS · doi:10.1542/peds.2021-054920 · Cited by 24 · see citing works
The future of artificial intelligence in intensive care: moving from predictive to actionable AI
Smit, J. M., Krijthe, J. H., van Bommel, J., Collaborators, T. C. I. F. I., van Genderen, M. E., Labrecque, J. A., Komorowski, M., Gommers, D. A. M. P. J., & Reinders, M. J. T. (2023) · Intensive Care Medicine · doi:10.1007/s00134-023-07102-y · Cited by 29 · see citing works
Framework for identifying drug repurposing candidates from observational healthcare data
Ozery-Flato, M., Goldschmidt, Y., Shaham, O., Ravid, S., & Yanover, C. (2020) · JAMIA Open · doi:10.1093/jamiaopen/ooaa048 · Cited by 30 · see citing works
Ponsonby, A. (2020) · International Journal of Epidemiology · doi:10.1093/ije/dyaa174 · Cited by 25 · see citing works
Overton, M., & Kleinschmit, S. W. (2021) · Teaching Public Administration · doi:10.1177/01447394211004990 · Cited by 30 · see citing works
“While some authors view data science activities as solely contributing to the analysis of data (Hern´an et al., 2019), the broader discipline is concerned with every step of the data to insight process (Donoho, 2017).”
BackgroundA scoping review of law enforcement drug seizures and overdose mortality in the United States
Cano, M. N., Timmons, P., Hooten, M., Sweeney, K. R., & Oh, S. (2024) · International Journal of Drug Policy · doi:10.1016/j.drugpo.2024.104321 · Cited by 29 · see citing works
The Target Trial: A Powerful Device Beyond Well-defined Interventions
Moreno‐Betancur, M. (2020) · Epidemiology · doi:10.1097/ede.0000000000001318 · Cited by 26 · see citing works
Improving child health through Big Data and data science
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“Three overarching approaches to analysis have been used: descriptive, predictive, and counterfactual.(28,29) Descriptive analysis utilizes conventional parametric and non-parametric statistics to provide quantitative estimates of central tendency and variability.”
Barmanray, R., Kyi, M., Worth, L. J., Colman, P. G., Churilov, L. P., Fazio, T. N., Rayman, G. A., Gonzalez, V., Hall, C., & Fourlanos, S. (2024) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgae051 · Cited by 28 · see citing works
Re-examining the Association Between E-Cigarette Use and Myocardial Infarction: A Cautionary Tale
Critcher, C. R., & Siegel, M. D. (2021) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2021.05.003 · Cited by 27 · see citing works
Shiba, K., Daoud, A., Kino, S., Nishi, D., Kondo, K., & Kawachi, I. I. (2021) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.13322 · Cited by 27 · see citing works
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Node Centrality Measures are a poor substitute for Causal InferencePreprint
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Reshaping the Arc of Quantitative Educational Research: It’s Time to Broaden Our Paradigm
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“Epidemiologists Hernan, Hsu, and Healy (2019) emphasize this point in a recent paper that concludes: “No AI will be worthy of the name without causal inference.””
BackgroundNielsen, R. O., Shrier, I., Casals, M., Nettel‐Aguirre, A., Møller, M., Bolling, C. S., Bittencourt, N. F. N., Clarsen, B. M., Wedderkopp, N., Soligard, T., et al. (2020) · Journal of Orthopaedic and Sports Physical Therapy · doi:10.2519/jospt.2020.9876 · Cited by 25 · see citing works
Types of Research Questions: Descriptive, Predictive, or Causal
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A framework for modeling human behavior in large-scale agent-based epidemic simulations
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“8 11 The importance of ABMS for studying the impact of behavioral health interventions has become particularly evident during the recent COVID-19 pandemic.”
BackgroundThe insight of why: Causal inference in Earth system science
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Explainable AI in healthcare: to explain, to predict, or to describe?
Carriero, A., de Hond, A., Cappers, B. C. M., Paulovich, F. V., Abeln, S., Moons, K. G. M., & van Smeden, M. (2025) · Diagnostic and Prognostic Research · doi:10.1186/s41512-025-00213-8 · Cited by 33 · see citing works
- Authors
- Hernán, M. A., Hsu, J., & Healy, B.
- Affiliations
- Harvard University (US)
- ORCID
- Healy, Brian
- Venue
- CHANCE
- Publisher
- Informa UK Limited
- Published
- 2019-01-02
- Volume
- 32
- Issue
- 1
- Pages
- 42-49
- ISSN
- 0933-2480 (ISSN-L)
- 1867-2280
- OpenAlex
- W2798958557
- Cited by
- 495
- References
- 0
- Citations by year
- 2026: 70 · 2025: 79 · 2024: 67 · 2023: 70 · 2022: 64 · 2021: 67 · 2020: 56 · 2019: 20 · 2018: 1 · 2012: 1
- FWCI
- 40.73
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- CHANCE (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
- Keywords
- causal inference, history of statistics, learning from data
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