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Multivariate mixed models accounting for don’t know options in ordinal data

Journal of the Royal Statistical Society Series A (Statistics in Society)(2025)10.1093/jrsssa/qnaf197Source: DataRank Database

Multivariate mixed models accounting for don’t know options in ordinal data is a research paper published in Journal of the Royal Statistical Society Series A (Statistics in Society) (2025). 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 (2 grants)Impact (FWCI 0.00)OA: hybridTopics (18)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 (2)

Maria Iannario ORCID,Ralitza Gueorguieva ORCID

Live enrichment

PubMed:41509862 PMC:PMC12778354 OpenAlex:https://openalex.org/W7117366251

Industrial Doctoral Network on Digital Finance

Grant: 101119635

Italian Ministry of University and Research

Grant: U54DA036151

FWCI

0.00

Citation Percentile

0.7%

hybridLicense: cc-by

journalhttps://doi.org/10.1093/jrsssa/qnaf197

publisherhttps://doi.org/10.1093/jrsssa/qnaf197

publisherhttps://academic.oup.com/jrsssa/advance-article-pdf/doi/10.1093/jrsssa/qnaf197/66130421/qnaf197.pdf

repositoryhttps://pubmed.ncbi.nlm.nih.gov/41509862

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC12778354/

Fields of Study

Economic and Environmental ValuationStatistical Methods and Bayesian InferenceAdvanced Causal Inference Techniques

Keywords

Ordinal dataMultivariate statisticsOrdinal regressionCovariateOrdinal ScaleInferencePopulationSelection biasMultivariate analysisRandom EffectsJoint ModelingCumulative Logit ModelLocation Scale ModelSemi-ordinal DataLocation Shift Model

Sustainable Development Goals

SDG 0: Good health and well-being