This paper introduces a new class of Cox models for dependent bivariate data. The impact of the covariate on the dependence of the variables is captured through the modification of their copula. Various classes of well-known copulas are stable under the model (Archimedean type and extreme value copulas), meaning that the role of the covariate acts in a simple and explicit way on the copula in the class; specific parametric classes are considered.
ClaytonDG. A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence. Biometrika. 1978; 65(1): 141–151.
2.
ClaytonDCuzickJ. Multivariate generalizations of the proportional hazards model. J R Statist Soc, Ser A (Gen). 1985; 148(2): 82–117.
3.
OakesD. Bivariate survival models induced by frailties. J Am Statist Assoc. 1989; 84, 406: 487–493.
4.
DeMasiRAQaqishBSenPK. A family of bivariate failure time distributions with proportional crude and conditional hazards. Comm Statist Theory Methods. 1998; 27(2): 365–384.
5.
ChoiYMatthewsDE. Accelerated life regression modelling of dependent bivariate time-to-event data. Can J Stat/La Revue Canadienne de Statistique. 2005; 33(3): 449–464.
6.
SaïdMGhazzaliNRivestL. Score tests for independence in semiparametric competing risks models. Lifetime Data Analysis. 2009; 15(4): 413–440.
7.
LindströmLSHallPHartmanMWiklundFGrönbergHCzeneK. Familial concordance in cancer survival: a Swedish population-based study. Lancet Oncol. 2007; 8(11): 1001–1006.
8.
GuptaRC. Reliability studies of bivariate distributions with exponential conditionals. Math Comp Mod. 2008; 47(9–10): 1009–1018.
9.
NelsenRB. An introduction to copulas. 2nd ed.New York: Springer; 2006.
10.
GrambschPMTherneauTM. Proportional hazards tests and diagnostics based on weighted residuals. Biometrika. 1994; 81(3): 515–526.
11.
ScailletO. A Kolmogorov–Smirnov type test for positive quadrant dependence. Can J Stat/La Revue Canadienne de Statistique. 2005; 33(3): 415–427.
12.
GenestCGhoudiKRivestLP. “Understanding relationships using copulas,” by Edward Frees and Emiliano Valdez, January 1998. N Am Act J. 1998; 2(3): 143–149.
13.
LiebscherE. Construction of asymmetric multivariate copulas. J Multivar Anal. 2008; 99: 2234–2250.
14.
TawnJA. Bivariate extreme value theory: models and estimation. Biometrika. 1988; 75(3): 397–415.
15.
AchibiMBroniatowskiM. Bivariate Cox model and copulas. arXiv:09111443. 2009; Electronic preprint; http://arxiv.org/abs/0911.1443.
16.
ResnickSI. Extreme values, regular variation, and point processes. vol. 4 of Applied Probability. A Series of the Applied Probability Trust. New York: Springer-Verlag; 1987.