Evidence map›Paper›PMID 36798366›Full record

ArticlebioRxiv : the preprint server for biology2024

Speeding up interval estimation for

Zhichao Xu, Chunlin Li, Sunyi Chi, Tianzhong Yang, Peng Wei

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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

5 · Who and what money

Authors and funding

5 authors.

Zhichao XuDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, U.S.A.ORCID 0000-0002-3935-8865
Chunlin LiDepartment of Statistics, Iowa State University, Ames, Iowa, 50011, U.S.A.ORCID 0000-0003-2989-8785
Sunyi ChiDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, U.S.A.ORCID 0000-0003-4112-2074
Tianzhong YangDivision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota 55455, U.S.A.ORCID 0000-0002-0162-7740
Peng WeiDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, U.S.A.ORCID 0000-0001-7758-6116

Funding

FRAMINGHAM HEART STUDY - YEAR 5 EXAM75N92019D00031 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · 2019 to 2024
$29.8M
Association analysis of rare variants with sequencing dataR01HL116720 · NHLBI · UNIVERSITY OF MINNESOTA · PI PAN, WEI, WEI, PENG · 2013 to 2020
$3.3M
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
–
NHLBI NIH HHS 75N92019D00031NHLBI NIH HHS N01 HC025195NHLBI NIH HHS R01 HL116720
6 · The paper itself

Abstract

Mediation analysis is a useful tool in investigating how molecular phenotypes such as gene expression mediate the effect of exposure on health outcomes. However, commonly used mean-based total mediation effect measures may suffer from cancellation of component-wise mediation effects in opposite directions in the presence of high-dimensional omics mediators. To overcome this limitation, we recently proposed a variance-based R-squared total mediation effect measure that relies on the computationally intensive nonparametric bootstrap for confidence interval estimation. In the work described herein, we formulated a more efficient two-stage, cross-fitted estimation procedure for the

Indexed as

Confidence intervalCross-FittingGene expressionIterative sure independence screeningMediation analysisR2 total mediation effect measure

Identifiers

PMID36798366
PMCPMC9934518

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.