참고문헌
- Anderson, K. M., Castelli, W. P. and Levy, D. (1987). Cholesterol and mortality. 30 years of follow-up from the Framingham study. Journal of American Medical Association, 257, 2176-2180. https://doi.org/10.1001/jama.1987.03390160062027
- Cheng, S. C., Wei, L. J. and Ying, Z. (1995). Analysis of transformation models with censored data. Biometrika, 82, 835-845. https://doi.org/10.1093/biomet/82.4.835
- Cho, G. Y. and Dashnyam, O. (2013). Generalized methods of moments in marginal models for longitudinal data with time-dependent covariates. Journal of the Korean Data & Information Science Society, 24, 877-883. https://doi.org/10.7465/jkdi.2013.24.4.877
- Daniels, S. R., McMahon, R .P., Obarzanek, E., Waclawiw, M. A., Similo, S. L., Biro, F. M., Schreiber, G. B., Kimm, S. Y., Morrison, J. A. and Barton, B. A. (1998). Longitudinal correlates of change in blood pressure in adolescent girls. Hypertension, 31, 97-103. https://doi.org/10.1161/01.HYP.31.1.97
- Diggle, P. J., Liang, K. Y. and Zeger S. L. (1994). Analysis of longitudinal data, Oxford University Press, Oxford.
- Genest, C., Ghoudi, K. and Rivest, L. P. (1995). A semiparametric estimation procedures of dependence parameters in multivariate families of distributions. Biometrika, 82, 543-552. https://doi.org/10.1093/biomet/82.3.543
- Genest, C. and MacKay, J. (1986). A joy of copulas: Bivariate distributions with uniform marginals. The American Statistician, 40, 280-283.
- Jeon J. Y. and Lee K. (2014) Review and discussion of marginalized random effects models. Journal of the Korean Data & Information Science Society, 25, 1263-1272. https://doi.org/10.7465/jkdi.2014.25.6.1263
- Joe, H. (1993). Parametric families of multivariate distributions with given margins. Journal of Multivariate Analysis, 46, 262-282. https://doi.org/10.1006/jmva.1993.1061
- Leon, A.R. andWu, B. (2011). Copula-based regression models for a bivariate mixed discrete and continuous outcome. Statistics in Medicine, 30, 175-185. https://doi.org/10.1002/sim.4087
- Lindsey, J. K. (1993). Models for repeated measurements, Oxford University Press, Oxford.
- Molenberghs, G. and Verbeke, G. (2005). Models for Discrete Longitudinal Data, Springer, New York.
- National Heart, Lung, and Blood Institute Growth and Health Research Group (NGHSRG) (1992). Obesity and cardiovascular disease risk factors in black and white girls: The NHLBI growth and health study. Americal Journal of Public Health, 82, 1613-1620. https://doi.org/10.2105/AJPH.82.12.1613
- National High Blood Pressure Education Program Working Group on High Blood Pressure in Children and Adolescents (NHBPEP Working Group) (2004). The fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents. Pediatrics, 114, 555-576. https://doi.org/10.1542/peds.114.2.S2.555
- Oakes, D. (1986). Semiparametric inference in a model for association in bivariate survival data. Biometrika, 73, 353-361.
- Obarzanek, E.,Wu, C. O., Cutler, J. A., Kavey, R. W., Pearson, R. W. and Daniels, S. R. (2010). Prevalence and incidence of hypertension in adolescent girls. Journal of Pediatrics, 157, 461-467. https://doi.org/10.1016/j.jpeds.2010.03.032
- Sklar, A. (1959). Fonctions de repartition an dimensions et leurs marges. Publications de L'Institute de Statistique de L'Universite de Paris, 8, 229-231.
- Song, P. X. K., Li, M. and Yuan, Y. (2009). Joint regression analysis of correlated data using Gaussian Copulas. Biometrics, 65, 60-68. https://doi.org/10.1111/j.1541-0420.2008.01058.x
- Thompson, D. R., Obarzanek, E., Franko, D. L., Barton, B. A., Morrison, J., Biro, F. M., Daniels, S. R. and Striegel-Moore, R. H. (2007). Childhood overweight and cardiovascular disease risk factors: The national heart, lung, and blood institute growth and health study. Journal of Pediatrics, 150, 18-25. https://doi.org/10.1016/j.jpeds.2006.09.039
- Wu, C. O. and Tian, X. (2013). Nonparametric estimation of conditional distribution functions and ranktracking probabilities with time-varying transformation models in longitudinal studies. Journal of the American Statistical Association, 108, 971-982. https://doi.org/10.1080/01621459.2013.808949
피인용 문헌
- 코플라함수를 이용한 극단치 강풍과 강수 분석 vol.28, pp.4, 2016, https://doi.org/10.7465/jkdi.2017.28.4.797