ArticleAmerican journal of epidemiology2024
Estimating Subgroup Effects in Generalizability and Transportability Analyses.
Article in American journal of epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 2 citations in OpenAlex.
- Using methods to extend inferences to specific target populations to improve the precision of subgroup analyses.Journal of clinical epidemiology · 2025Trial
- Regression-based estimation of heterogeneous treatment effects when extending inferences from a randomized trial to a target population.European journal of epidemiology · 2023Trial
- Generalizing Conditional Average Treatment Effects From Nested Randomized Trials to Trial-Eligible Individuals.Statistics in medicine · 2026Article
- Estimating and discovering heterogeneous treatment effects using machine learning in epidemiological studies: a practical guide.International journal of epidemiology · 2026Review
- Estimating and Evaluating Counterfactual Prediction Models.Statistics in medicine · 2025Article
- Development and Validation of Prediction Models for the Diagnosis of Autism Spectrum Disorder in a Korean General Population.JAACAP open · 2025Article
- Machine-learning approaches to predict individualized treatment effect using a randomized controlled trial.European journal of epidemiology · 2025Article
- Transporting: What Is It and How Do You Do It?Current epidemiology reports · 2025Article
- Quantifying and reducing inequity in average treatment effect estimation.BMC medical research methodology · 2023Article
- Assessments of the Value of New Interventions Should Include Health Equity Impact.PharmacoEconomics · 2022Article
- Estimation of DAPT Study Treatment Effects in Contemporary Clinical Practice: Findings From the EXTEND-DAPT Study.Circulation · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Methods for extending-generalizing or transporting-inferences from a randomized trial to a target population involve conditioning on a large set of covariates that is sufficient for rendering the randomized and nonrandomized groups exchangeable. Yet, decision makers are often interested in examining treatment effects in subgroups of the target population defined in terms of only a few discrete covariates. Here, we propose methods for estimating subgroup-specific potential outcome means and average treatment effects in generalizability and transportability analyses, using outcome model--based (g-formula), weighting, and augmented weighting estimators. We consider estimating subgroup-specific average treatment effects in the target population and its nonrandomized subset, and we provide methods that are appropriate both for nested and non-nested trial designs. As an illustration, we apply the methods to data from the Coronary Artery Surgery Study (North America, 1975-1996) to compare the effect of surgery plus medical therapy versus medical therapy alone for chronic coronary artery disease in subgroups defined by history of myocardial infarction.
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.