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Implications of confounding from unmodeled interactions between explanatory variables when using latent variable regression models to make inferences

Journal of Chemometrics(2024)10.1002/cem.3531Source: DataRank Database

Implications of confounding from unmodeled interactions between explanatory variables when using latent variable regression models to make inferences is a research paper published in Journal of Chemometrics (2024). On theSindex it has a DataRank of 0. It has been cited 3 times.

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Open Access3 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (2 grants)Impact (FWCI 0.58)OA: hybridTopics (14)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)

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Authors (5)

Warren S. Vidar ORCID,Tim U. H. Baumeister ORCID,Roger G. Linington ORCID,Nadja B. Cech ORCID,Olav M. Kvalheim ORCID

Live enrichment

PubMed:39239103 PMC:PMC11374105 OpenAlex:https://openalex.org/W4390828111

Office of Dietary Supplements

Grant: U41 AT008178

NCCIH NIH HHS

Grant: U41 AT008718

FWCI

0.58

Citation Percentile

0.6%

Citation Trend

2024

2026

hybridLicense: cc-by

journalhttps://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/cem.3531

publisherhttps://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/cem.3531

publisherhttps://analyticalsciencejournals.onlinelibrary.wiley.com/doi/pdf/10.1002/cem.3531

publisherhttps://analyticalsciencejournals.onlinelibrary.wiley.com/doi/full-xml/10.1002/cem.3531

journalhttps://doi.org/10.1002/cem.3531

Fields of Study

Spectroscopy and Chemometric AnalysesMetabolomics and Mass Spectrometry StudiesAdvanced Statistical Methods and Models

Keywords

Latent variableConfoundingEconometricsRegression analysisStatisticsRegressionVariable (mathematics)Latent variable modelMathematicsLinear regressionComputer science

Sustainable Development Goals

SDG 0: Responsible consumption and production