- 期刊
- OpenAccess
Copula-based Logistic Regression Models for Bivariate Binary Responses
並列摘要
The association between bivariate binary responses has been studied using Pearson's correlation coefficient, odds ratio, and tetrachoric correlation coefficient. This paper introduces a copula to model the association. Numerical comparisons between the proposed method and the existing methods are presented. Results show that these methods are comparative. However, the copula method has a clearer interpretation and is easier to extend to bivariate responses with three or more ordinal categories. In addition, a goodness-of-fit test for the selection of a model is performed. Applications of the method on two real data sets are also presented.
延伸閱讀
- 王清雲、趙強孫、陳瑞照（2004）。Review of Inverse Probability Weighted Estimation in Logistic Regression with Incomplete Covariates。智慧科技與應用統計學報，2(1)，1-15。https://doi.org/10.29807/JTITAS.200406.0001
- Lalonde, T. L., Nguyen, A. Q., Yin, J. Q., Irimata, K., & Wilson, J. R. (2013). Modeling Correlated Binary Outcomes with Time-Dependent Covariates. Journal of Data Science, 11(4), 715-738. https://doi.org/10.6339/JDS.2013.11(4).1195
- Yang, C. Y. (2012). Estimation of Linear Regression Models with Serially Correlated Errors. Journal of Data Science, 10(4), 723-755. https://doi.org/10.6339/JDS.2012.10(4).1106
- Lee, C. Y. (2008). A Comparison of Optimization Methods for Large-scale L1-regularized Logistic Regression [master's thesis, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU.2008.01406
- Kuo, W. T., & Shen, W. H. (2000). Tests for Response Probability in Multiple Logistic Regression Models. 東海管理評論, 2(1), 63-74. https://doi.org/10.29724/TMR.200011.0004