The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Maximum Likelihood Variance Components Estimation for Binary Data
Abstract
We consider a class of probit-normal models for binary data and describe ML and REML estimation of variance components for that class as well as best prediction for the realized values of the random effects. ML estimates are calculated using an EM algorithm; for complicated models EM includes a Gibbs step. The computations are illustrated through two examples.
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Cites
Handbook of Mathematical Functions
McQuarrie, D. A. (1966) · American Journal of Physics · doi:10.1119/1.1972842 · Cited by 40,433
Sampling-based approaches to calculating marginal densities
Gelfand, A. E., & Smith, A. F. M. (1990) · Journal of the American Statistical Association · doi:10.1080/01621459.1990.10476213 · Cited by 6,606
Searle, S. R., Casella, G., & McCulloch, C. E. (1992) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316856 · Cited by 1,926
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Cited by
An introduction to MCMC for machine learning.
Andrieu, C., de Freitas, N., Doucet, A., & Jordan, M. I. (2003) · Machine Learning · doi:10.1023/a:1020281327116 · Cited by 2,451
The EM Algorithm—an Old Folk-song Sung to a Fast New Tune
Meng, X.-L., & Van Dyk, D. (1997) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00082 · Cited by 802
Generalized Linear Mixed Models
McCulloch, C. E. (2001) · Encyclopedia of Environmetrics · doi:10.1002/9780470057339.vag009 · Cited by 295
Self-citationThe power of the classical twin study to resolve variation in threshold traits
Neale, M. C., Eaves, L. J., & Kendler, K. S. (1994) · Behavior Genetics · doi:10.1007/bf01067191 · Cited by 287
Standard Errors of Prediction in Generalized Linear Mixed Models
Booth, J. G., & Hobert, J. P. (1998) · Journal of the American Statistical Association · doi:10.1080/01621459.1998.10474107 · Cited by 133
Metadata
- Authors
- McCulloch, C. E.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1994-03
- Volume
- 89
- Issue
- 425
- Pages
- 330-335
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2008197960
- Cited by
- 229
- References
- 3
- FWCI
- 7.89
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
