Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.

Bayesian Nonparametric Model for Heterogeneous Treatment Effects With Zero‐Inflated Data

Statistics in Medicine(2024)10.1002/sim.10266Source: DataRank Database

Bayesian Nonparametric Model for Heterogeneous Treatment Effects With Zero‐Inflated Data is a research paper published in Statistics in Medicine (2024). On theSindex it has a DataRank of 0. It has been cited 1 time.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access1 citations

Download PDF

Cite:

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (14 grants)Impact (FWCI 0.54)OA: greenTopics (27)IDs (PubMed, PMC, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

Run a calibrated FAIR evaluation for this paper →

We only score data papers we can read in full — never from an abstract alone.

Authors (4)

Yisheng Li ORCID,Ting Xu ORCID,Zhongxing Liao ORCID,Chanmin Kim ORCID

Live enrichment

PubMed:39608809 PMC:PMC11834965 OpenAlex:https://openalex.org/W4404798477

National Institutes of Health

Grant: 1R01HL157273‐01

Cancer Prevention and Research Institute of Texas

Grant: RP240440

National Research Foundation of Korea

Grant: NRF‐2020R1F1A1A01048168

National Research Foundation of Korea

Grant: NRF‐2022R1F1A1062904

National Research Foundation of Korea

Grant: RS‐2024‐00407300

NHLBI NIH HHS

Grant: R01 HL157273

US National Institutes of Health/National Cancer Institute

Grant: P30CA016672-45

US National Institutes of Health/National Cancer Institute

Grant: P50CA217674-03

National Research Foundation of Korea

Grant: NRF-2020R1F1A1A01048168

National Research Foundation of Korea

Grant: NRF-2022R1F1A1062904

NCI NIH HHS

Grant: P30 CA016672

NCI NIH HHS

Grant: P50 CA217674

National Research Foundation of Korea

Grant: RS-2024-00407300

US National Institutes of Health

Grant: 1R01HL157273-01

FWCI

0.54

Citation Percentile

0.7%

Citation Trend

2025

greenLicense: http://onlinelibrary.wiley.com/termsAndConditions#vor

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC11834965/pdf/nihms-2048586.pdf

publisherhttps://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.10266

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC11834965/

journalhttps://doi.org/10.1002/sim.10266

Fields of Study

Statistical Methods and InferenceBayesian Methods and Mixture ModelsStatistical Methods and Bayesian Inference

MeSH Terms

Treatment Effect HeterogeneityBayes TheoremComputer SimulationHumansModels, StatisticalBiasTreatment OutcomeStatistics, NonparametricPrecision Medicine

Keywords

CovariateDirichlet processNonparametric statisticsCausal inferenceStatisticsEconometricsBayesian probabilityComputer scienceInferenceMathematicsArtificial intelligenceMissing At RandomHeterogeneous EffectsHigh‐sensitivity Cardiac Troponin TEnriched Dirichlet Process

Sustainable Development Goals

SDG 0: Good health and well-being