Evidence map›Paper›PMID 36349247›Full record

ArticleStatistica Sinica2022

STATISTICAL INFERENCE IN QUANTILE REGRESSION FOR ZERO-INFLATED OUTCOMES.

Wodan Ling, Bin Cheng, Ying Wei, Joshua Z Willey, Ying Kuen Cheung

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Statistica Sinica, 2022. 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

5 authors.

Wodan LingFred Hutchinson Cancer Research Center.
Bin ChengColumbia University.
Ying WeiColumbia University.
Joshua Z WilleyColumbia University.
Ying Kuen CheungColumbia University.

Funding

Multi-omics approaches for gene discovery in Alzheimer's Disease.RF1AG072272 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI IONITA, IULIANA, WEI, YING · 2021 to 2021
$1.6M
Develop quantile analysis tools for sequencing and eQTL studiesR01HG008980 · NHGRI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI WEI, YING · 2016 to 2019
$1.6M
NHGRI NIH HHS R01 HG008980NIA NIH HHS RF1 AG072272
6 · The paper itself

Abstract

An extension of quantile regression is proposed to model zero-inflated outcomes, which have become increasingly common in biomedical studies. The method is flexible enough to depict complex and nonlinear associations between the covariates and the quantiles of the outcome. We establish the theoretical properties of the estimated quantiles, and develop inference tools to assess the quantile effects. Extensive simulation studies indicate that the novel method generally outperforms existing zero-inflated approaches and the direct quantile regression in terms of the estimation and inference of the heterogeneous effect of the covariates. The approach is applied to data from the Northern Manhattan Study to identify risk factors for carotid atherosclerosis, measured by the ultrasound carotid plaque burden.

Indexed as

Constrained post-estimation smoothingNonnormal asymptotic distributionQuantile regressionZero-inflated outcomes

Identifiers

PMID36349247
PMCPMC9640181

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.