ArticleJournal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America2018
Estimating Individual Treatment Effect in Observational Data Using Random Forest Methods.
Article in Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
49 citing papers in PubMed.
- Machine learning methods for estimating personalized treatment effects-insights on validity from two large trials.American journal of epidemiology · 2026Article
- An individual treatment effect approach to predict response to mineralocorticoid receptor antagonists in patients with heart failure and reduced ejection fraction.European journal of heart failure · 2025Article
- Individualized prescriptive inference in ischaemic stroke.Nature communications · 2025Article
- Precision ecology for targeted conservation action.Nature ecology & evolution · 2025Review
- American Association for Thoracic Surgery Quality Gateway: A surgeon case study of its application in adult cardiac surgery for quality assurance.The Journal of thoracic and cardiovascular surgery · 2025Article
- Development of American Association for Thoracic Surgery Quality Gateway outcome models, analytics, and visualizations for quality assurance.The Journal of thoracic and cardiovascular surgery · 2025Article
- SPRINT Treatment Among Adults With Chronic Kidney Disease From 2 Large Health Care Systems.JAMA network open · 2025Article
- Extended fiducial inference for individual treatment effects via deep neural networks.Statistics and computing · 2025Article
- Adjuvant Therapy after Esophagectomy for Esophageal Cancer: Who Needs It?: Multi-institution Worldwide Observational Study.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2024Article
- Machine Learning Methods to Estimate Individualized Treatment Effects for Use in Health Technology Assessment.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Review
- Interpretable artificial intelligence to optimise use of imatinib after resection in patients with localised gastrointestinal stromal tumours: an observational cohort study.The Lancet. Oncology · 2024Observational
- Heterogeneous treatment effect estimation for observational data using model-based forests.Statistical methods in medical research · 2024Article
- Machine learning and personalized nutrition: a promising liaison?European journal of clinical nutrition · 2024Article
- A new method for clustered survival data: Estimation of treatment effect heterogeneity and variable selection.Biometrical journal. Biometrische Zeitschrift · 2024Article
- A general framework for subgroup detection via one-step value difference estimation.Biometrics · 2023Article
- Determinants of outpatient substance use disorder treatment length-of-stay and completion: the case of a treatment program in the southeast U.S.Scientific reports · 2023Article
- Causal Bayesian machine learning to assess treatment effect heterogeneity by dexamethasone dose for patients with COVID-19 and severe hypoxemia.Scientific reports · 2023Article
- Estimating individualized treatment effects from randomized controlled trials: a simulation study to compare risk-based approaches.BMC medical research methodology · 2023Article
- Assessing the Most Vulnerable Subgroup to Type II Diabetes Associated with Statin Usage: Evidence from Electronic Health Record Data.Journal of the American Statistical Association · 2023Article
- Retrospective cohort study to devise a treatment decision score predicting adverse 24-month radiological activity in early multiple sclerosis.Therapeutic advances in neurological disorders · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Estimation of individual treatment effect in observational data is complicated due to the challenges of confounding and selection bias. A useful inferential framework to address this is the counterfactual (potential outcomes) model, which takes the hypothetical stance of asking what if an individual had received
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.