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A comparison of some existing and novel methods for integrating historical models to improve estimation of coefficients in logistic regression

Journal of the Royal Statistical Society Series A (Statistics in Society)(2024)10.1093/jrsssa/qnae093Source: DataRank Database

A comparison of some existing and novel methods for integrating historical models to improve estimation of coefficients in logistic regression is a research paper published in Journal of the Royal Statistical Society Series A (Statistics in Society) (2024). On theSindex it has a DataRank of 0. It has been cited 1 time.

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Enrichment:Funding (1 grants)Impact (FWCI 0.51)OA: greenTopics (26)IDs (PubMed, PMC, OpenAlex)Annotations (1)SDGs (1)

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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 (2)

Pedro Orozco del Pino,Philip S. Boonstra ORCID

Live enrichment

PubMed:39810879 PMC:PMC11728056 OpenAlex:https://openalex.org/W4402812678

National Institutes of Health

Grant: P30 CA046592

FWCI

0.51

Citation Percentile

0.7%

Citation Trend

2024

greenLicense: https://academic.oup.com/pages/standard-publication-reuse-rights

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC11728056/pdf/qnae093.pdf

publisherhttps://academic.oup.com/jrsssa/article-pdf/188/1/46/59315928/qnae093.pdf

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC11728056/

journalhttps://doi.org/10.1093/jrsssa/qnae093

Fields of Study

Statistical Methods and Bayesian InferenceStatistical Distribution Estimation and ApplicationsStatistical Methods and InferenceMedicineMathematics

Keywords

Logistic regressionCovariateEconometricsComputer scienceBayesian probabilityStatisticsEstimationVariance (accounting)Sample (material)Statistical modelSample size determinationMachine learningArtificial intelligenceMathematicsEngineeringData integrationModel IntegrationSaddle PointConstrained Maximum LikelihoodGeneralized Integration ModelSensible Adaptive Bayes

Sustainable Development Goals

SDG 0: Good health and well-being