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Approximate and Pseudo-Likelihood Analysis for Logistic Regression Using External Validation Data to Model Log Exposure

UNC Libraries(2021)10.17615/hva3-dy79Source: DataRank Database

Approximate and Pseudo-Likelihood Analysis for Logistic Regression Using External Validation Data to Model Log Exposure is a research paper published in UNC Libraries (2021). On theSindex it has a DataRank of 0.

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (3 grants)Impact (FWCI 0.00)OA: greenTopics (15)IDs (PubMed, OpenAlex)

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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)

Lawrence L. Kupper ORCID,Robert H. Lyles ORCID

Live enrichment

PubMed:19910364 OpenAlex:https://openalex.org/W4299510199

National Institutes of Health

Grant: 1RC4NR012527-01

Accessible Handling of Misclassified or Missing Binary Variables in CER Studies

National Institutes of Health

Grant: 5R01ES012458-07

Analytical Methods: Environmental/Reproductive Epidemiology

National Institutes of Health

Grant: 5UL1TR000454-07

Atlanta Clinical and Translational Science Institute (ACTSI) Renewal

FWCI

0.00

Citation Percentile

0.2%

greenLicense: Springer TDM

repositoryhttps://doi.org/10.17615/hva3-dy79

https://doi.org/10.1007/s13253-012-0115-9

https://cdr.lib.unc.edu/downloads/0r967c674

https://dx.doi.org/10.17615/hva3-dy79

https://pubmed.ncbi.nlm.nih.gov/24027381

Fields of Study

Advanced Statistical Methods and Models0101 mathematics01 natural sciences

Keywords

Logistic regressionStatisticsRegression analysisComputer scienceEconometricsMathematicsvalidationconsistencymultiplicative measurement errorlikelihoodprobitApplications of statistics to environmental and related topics