Evidence map›Paper›PMID 35125524›Full record

ArticleQuarterly of applied mathematics2019

LOCALIZING DIFFERENTIALLY EVOLVING COVARIANCE STRUCTURES VIA SCAN STATISTICS.

Ronak Mehta, Hyunwoo J Kim, Shulei Wang, Sterling C Johnson, Ming Yuan, Vikas Singh

Abstract read
In one paragraph

Article in Quarterly of applied mathematics, 2019. 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

6 authors.

Ronak MehtaDepartment of Computer Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA.
Hyunwoo J KimDepartment of Computer Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA.
Shulei WangDepartment of Statistics, Columbia University, New York, NY 10027, USA.
Sterling C JohnsonAlzheimer's Disease Research Center, University of Wisconsin-Madison, Madison, WI 53792, USA.
Ming YuanDepartment of Statistics, Columbia University, New York, NY 10027, USA.
Vikas SinghDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA.

Funding

Wisconsin Alzheimer's Disease Research CenterP30AG062715 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI AMY J. KIND · 2019 to 2026
$34.5M
The Longitudinal Course of Neural Function and Amyloid in People At Risk for ADR01AG021155 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Sterling C Johnson · 2004 to 2026
$27.0M
Wisconsin Alzheimer's Disease Research CenterP50AG033514 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI CHAPPELL, RICHARD J · 2009 to 2018
$16.2M
TrainingU54AI117924 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI CRAVEN, MARK W. · 2014 to 2018
$11.3M
Bio-Data Science Training ProgramT32LM012413 · NLM · UNIVERSITY OF WISCONSIN-MADISON · PI DEWEY, COLIN NOEL, GOULD, MICHAEL N · 2016 to 2020
$1.5M
Maximizing Power in AD Clinical Trials via Multimodal Machine LearningR01AG040396 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI SINGH, VIKAS · 2012 to 2015
$1.1M
Manifold-valued statistical models for longitudinal morphometic analysis in preclinical Alzheimer's disease (AD)R01EB022883 · NIBIB · UNIVERSITY OF WISCONSIN-MADISON · PI JOHNSON, STERLING C, SINGH, VIKAS · 2016 to 2018
$995k
NIAID NIH HHS U54 AI117924NIA NIH HHS P30 AG062715NIA NIH HHS P50 AG033514NIA NIH HHS R01 AG021155NIA NIH HHS R01 AG040396NIBIB NIH HHS R01 EB022883NLM NIH HHS T32 LM012413
6 · The paper itself

Abstract

Recent results in coupled or temporal graphical models offer schemes for estimating the relationship structure between features when the data come from related (but distinct) longitudinal sources. A novel application of these ideas is for analyzing group-level differences, i.e., in identifying if

Identifiers

PMID35125524
PMCPMC8813049

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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.