The DOI matches its Crossref record.
A Method for Generating High-Dimensional Multivariate Binary Variates
Abstract
Examples are given of the need for simulating correlated binary variates with different given marginal expectations and pairwise correlations. An algorithm is then presented for generating such variates. The algorithm may be used to generate variates of any dimension.
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Cited by
Wu, S., Crespi, C. M., & Wong, W. K. (2012) · Contemporary Clinical Trials · doi:10.1016/j.cct.2012.05.004 · Cited by 272
Asymptotic variability of (multilevel) multirater kappa coefficients
Vanbelle, S. (2019) · Statistical Methods in Medical Research · doi:10.1177/0962280218794733 · Cited by 33
Metadata
- Authors
- Emrich, L. J., & Piedmonte, M. R.
- Venue
- The American Statistician
- Publisher
- Informa UK Limited
- Published
- 1991-11
- Volume
- 45
- Issue
- 4
- Pages
- 302-304
- ISSN
- 0003-1305 (ISSN-L)
- 1537-2731
- OpenAlex
- W2099175767
- Cited by
- 193
- References
- 0
- FWCI
- 0.89
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A Method for Generating High-Dimensional Multivariate Binary Variates. https://app.cochat.ai/papers/10.1080/00031305.1991.10475828
- The paper
- Emrich, L. J., & Piedmonte, M. R. (1991). A Method for Generating High-Dimensional Multivariate Binary Variates. The American Statistician. https://doi.org/10.1080/00031305.1991.10475828
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
