Evidence map›Paper›PMID 42461616›Full record

ArticleJournal of the Royal Statistical Society. Series B, Statistical methodology2026

Augmented balancing weights as linear regression.

David Bruns-Smith, Oliver Dukes, Avi Feller, Elizabeth L Ogburn

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the Royal Statistical Society. Series B, Statistical methodology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Regularizing Extrapolation in Causal Inference.Proceedings of machine learning research · 2026
    Article
  3. Stabilized Inverse Probability Weighting via Isotonic Calibration.Proceedings of machine learning research · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

David Bruns-SmithGraduate School of Business, Stanford University, Stanford, CA, USA.
Oliver DukesDepartment of Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.ORCID https://orcid.org/0000-0002-9145-3325
Avi FellerGoldman School of Public Policy, Department of Statistics, University of California, Berkeley, CA, USA.ORCID https://orcid.org/0000-0001-7319-5468
Elizabeth L OgburnDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We provide a novel characterization of augmented balancing weights, also known as automatic debiased machine learning. These popular

Indexed as

balancing weightsdebiased machine learningdoubly robust estimationundersmoothing

Identifiers

PMID42461616
PMCPMC13370344

What OpenQuestion holds

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Registered trials

None linked

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.