A Composite Likelihood Approach to Multivariate Survival Data

This paper is about the statistical analysis of multivariate survival data. We discuss the additive and multiplicative frailty models which have been the most popular models for multivariate survival data. As an alternative to the additive and multiplicative frailty models, we propose basing inference on a composite likelihood function that only requires modelling of the marginal distribution of pairs of failure times. Each marginal distribution of a pair of failure times is here assumed to follow a shared frailty model. The method is illustrated with a real-life example.

[1]  T. Louis,et al.  Inferences on the association parameter in copula models for bivariate survival data. , 1995, Biometrics.

[2]  J. Hoffmann-jorgensen,et al.  The general marginal problem , 1987 .

[3]  Nancy Flournoy,et al.  Assessment of Dependence In the Life Times of Twins , 1992 .

[4]  P. Hougaard.  A class of multivanate failure time distributions , 1986 .

[5]  D. Clayton.  A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence , 1978 .

[6]  Richard D. Gill,et al.  A counting process approach to maximum likelihood estimation in frailty models , 1992 .

[7]  C. Genest,et al.  A semiparametric estimation procedure of dependence parameters in multivariate families of distributions , 1995 .

[8]  Joanna H. Shih,et al.  Modeling multivariate discrete failure time data. , 1998, Biometrics.

[9]  Jørgen Holm Petersen,et al.  An additive frailty model for correlated life times. , 1998, Biometrics.

[10]  A. Wald.  Note on the Consistency of the Maximum Likelihood Estimate , 1949 .

[11]  S. Lele,et al.  A Composite Likelihood Approach to Binary Spatial Data , 1998 .

[12]  P. Andersen,et al.  Genetic and environmental influences on premature death in adult adoptees. , 1988, The New England journal of medicine.

[13]  T. Sweeting.  Uniform Asymptotic Normality of the Maximum Likelihood Estimator , 1980 .

[14]  P. J. Huber.  The behavior of maximum likelihood estimates under nonstandard conditions , 1967 .

[15]  H. White.  Maximum Likelihood Estimation of Misspecified Models , 1982 .

[16]  P. Hougaard,et al.  Frailty models for survival data , 1995, Lifetime data analysis.

[17]  Russell C. H. Cheng,et al.  Non-regular maximum likelihood problems , 1995 .

[18]  A. Yashin,et al.  Correlated individual frailty: an advantageous approach to survival analysis of bivariate data. , 1995, Mathematical population studies.

[19]  L. J. Wei,et al.  Regression analysis of multivariate incomplete failure time data by modeling marginal distributions , 1989 .