Factor copula models for item response data
- Submitting institution
-
The University of East Anglia
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 182619034
- Type
- D - Journal article
- DOI
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10.1007/s11336-013-9387-4
- Title of journal
- Psychometrika
- Article number
- -
- First page
- 126
- Volume
- 80
- Issue
- 1
- ISSN
- 0033-3123
- Open access status
- Out of scope for open access requirements
- Month of publication
- March
- Year of publication
- 2015
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
1
- Research group(s)
-
-
- Citation count
- 16
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This extremely highly-cited paper (Field Citation Rate of 7.81; dimensions.ai), in the top psychometrics journal, proposes a novel and general latent variable model for high-dimensional data. This research is the result of collaboration with an international collaborator (DOI 10.1515/demo-2018-0016), supported by NERC Canada. Has been downloaded over 900 times, and has impacted on research in statistics (e.g., Genton, King Abdullah; Czado, Munich; Athanasopoulos, Monash) and a diverse set of application domains including psychology (Maydeu-Olivares, Carolina), actuarial science (Hua, Illinois), and carbon finance (Zhang, McGill). Prof Genest (McGill) states: "Factor copula model approach holds great promise" (DOI 10.1515/demo-2016-0005 ).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -