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Causal Inference using Multivariate Generalized Linear Mixed-Effects Models with Longitudinal Data

arXiv (Cornell University)(2023)10.48550/arxiv.2303.02201Source: DataRank Database

Causal Inference using Multivariate Generalized Linear Mixed-Effects Models with Longitudinal Data is a research paper published in arXiv (Cornell University) (2023). On theSindex it has a DataRank of 0.

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (2 grants)OA: greenTopics (25)IDs (PubMed, OpenAlex)SDGs (2)

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Findable (1/2)

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Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (5)

Ji-Soo Kim ORCID,Laura K. Hummers ORCID,Ami A. Shah ORCID,Scott L. Zeger ORCID,Yizhen Xu ORCID

Live enrichment

PubMed:30945415 OpenAlex:https://openalex.org/W4323547457

National Institutes of Health

Grant: 5K24AR080217-04

Harnessing multivariate patient- and population-level disease trajectories to predict major clinical events in scleroderma

National Institutes of Health

Grant: 1P30AR070254-01

Johns Hopkins Rheumatic Diseases Resource-based Core Center

greenLicense: cc-by-nc-nd

repositoryhttps://arxiv.org/pdf/2303.02201

repositoryhttp://arxiv.org/abs/2303.02201

repositoryhttps://doi.org/10.48550/arxiv.2303.02201

https://dx.doi.org/10.48550/arxiv.2303.02201

Fields of Study

Advanced Causal Inference TechniquesStatistical Methods in Clinical TrialsStatistical Methods and InferenceMethodology (stat.ME)FOS: Computer and information sciences0101 mathematics01 natural sciences

Keywords

Counterfactual thinkingObservational studyMultivariate statisticsCausal inferenceConfoundingEconometricsBayesian probabilityGeneralized linear mixed modelLatent variableBayesian inferenceMissing dataComputer scienceMathematicsStatisticsPsychologyMethodology (stat.ME)FOS: Computer and information sciencesStatistics - Methodology

Sustainable Development Goals

SDG 3: 3. Good healthSDG 0: Good health and well-being