Evidence map›Paper›PMID 42266456›Full record

ArticleBiometrika2026

Finding distributions that differ, with false discovery rate control.

Yonghoon Lee, Edgar Dobriban, Eric J Tchetgen Tchetgen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biometrika, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Yonghoon LeeDepartment of Statistics and Data Science, The Wharton School, University of Pennsylvania, 265 South 37th Street, Philadelphia, Pennsylvania 19104, U.S.A.
Edgar DobribanDepartment of Statistics and Data Science, The Wharton School, University of Pennsylvania, 265 South 37th Street, Philadelphia, Pennsylvania 19104, U.S.A.
Eric J Tchetgen TchetgenDepartment of Statistics and Data Science, The Wharton School, University of Pennsylvania, 265 South 37th Street, Philadelphia, Pennsylvania 19104, U.S.A.

Funding

SOCIAL AND ECONOMIC PREDICTORS OF PHYSICAL AND COGNITIVE FUNCTIONP01AG041710 · NIA · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Julia Katherine Rohr · 2013 to 2026
$37.3M
Novel Designs and Methods to Remove Hidden Confounding Bias in Health SciencesR01AG065276 · NIA · UNIVERSITY OF PENNSYLVANIA · PI TCHETGEN TCHETGEN, ERIC JOEL · 2020 to 2024
$2.4M
Theory and methods for mediation and interactionR01CA222147 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI TCHETGEN TCHETGEN, ERIC JOEL, VANDERWEELE, TYLER · 2018 to 2022
$2.1M
Accounting for Hidden Bias in Vaccine Studies: A Negative Control FrameworkR01GM139926 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SHI, XU, TCHETGEN TCHETGEN, ERIC JOEL · 2021 to 2024
$1.5M
NCI NIH HHS R01 CA222147NIA NIH HHS P01 AG041710NIA NIH HHS R01 AG065276NIGMS NIH HHS R01 GM139926
6 · The paper itself

Abstract

We consider the problem of comparing a reference distribution with several other distributions. Given a sample from both the reference and the comparison groups, we aim to identify the comparison groups whose distributions differ from that of the reference group. Viewing this as a multiple-testing problem, we introduce a methodology that provides exact, distribution-free control of the false discovery rate. To do so, we introduce the concept of

Indexed as

Distribution-free inferenceFalse discovery rateMultiple testing

Identifiers

PMID42266456
PMCPMC13245922

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.