A Multivariate Bernoulli-Based Sampling Method for Multi-Label Data with Application to Meta-Research
Develops a multivariate Bernoulli sampling approach for research datasets in which records carry multiple overlapping labels.
Preprint; this version has not been peer reviewed.
Open-science resources
Resource verification & source notes
- Earlier preprint: Matched title / source version grouping.
- Preprint: Public preprint record in the saved source catalogue. No final journal article identified as of retrieval.
Publication details
Research themes
Author affiliations & identifiers
- Simon Chung: Arkansas Children's Research Institute; Arkansas Children's Research Institute, 13 Children's Way, Little Rock, AR 72202, United States; University of Arkansas for Medical Sciences - Department of Biostatistics; University of Arkansas for Medical Sciences - Department of Biostatistics, 4301 West Markham Street, Little Rock, AR 72205, United States
- Colby Vorland: Indiana University Bloomington; Indiana University Bloomington, Dept of Biology, 100 South Indiana Ave., Bloomington, IN 47405, United States
- Donna L. Maney: Independent - affiliation not provided to SSRN
- Andrew W. Brown: Independent - affiliation not provided to SSRN · ORCID https://orcid.org/0000-0002-1758-8205