Marginalized random-effects models for clustered binomial data through innovative link functions
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Economics and Econometrics,Social Sciences (miscellaneous),Modeling and Simulation,Statistics and Probability,Analysis
Link
https://link.springer.com/content/pdf/10.1007/s10182-021-00400-0.pdf
Reference57 articles.
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3. Celeux, G., Hurn, M., Robert, C.P.: Computational and inferential difficulties with mixture posterior distributions. J. Am. Stat. Assoc. 95(3), 957–979 (2000)
4. Chan, J.S., Kuk, A.Y.: Maximum likelihood estimation for probit-linear mixed models with correlated random effects. Biometrics 53(1), 86–97 (1997)
5. Chao, W.H., Palta, M., Young, T.: Effect of omitted confounders on the analysis of correlated binary data. Biometrics 53(2), 678–89 (1997)
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