Evidence map›Paper›PMID 40678203›Full record

ArticleJournal of the American Statistical Association2025

Controlling the False Split Rate in Tree-Based Aggregation.

Simeng Shao, Jacob Bien, Adel Javanmard

Abstract read
In one paragraph

Article in Journal of the American Statistical Association, 2025. 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.

Simeng ShaoAmazon, Seattle.
Jacob BienData Sciences and Operations, University of Southern California.
Adel JavanmardData Sciences and Operations, University of Southern California.

Funding

A Modeling Framework for Multi-View Data, with Applications to the Pioneer 100 Study and Protein Interaction NetworksR01GM123993 · NIGMS · UNIVERSITY OF WASHINGTON · PI BIEN, JACOB, WITTEN, DANIELA · 2017 to 2020
$1.3M
NIGMS NIH HHS R01 GM123993
6 · The paper itself

Abstract

In many domains, data measurements can naturally be associated with the leaves of a tree, expressing the relationships among these measurements. For example, companies belong to industries, which in turn belong to ever coarser divisions such as sectors; microbes are commonly arranged in a taxonomic hierarchy from species to kingdoms; street blocks belong to neighborhoods, which in turn belong to larger-scale regions. The problem of tree-based aggregation that we consider in this paper asks which of these tree-defined subgroups of leaves should really be treated as a single entity and which of these entities should be distinguished from each other. We introduce the

Indexed as

false discovery ratehierarchyMultiple testingrare features

Identifiers

PMID40678203
PMCPMC12266672

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.