: The long-term objective of this research is the development of sound methodologies which will facilitate studying the role of both genetic and environmental factors in cardiovascular disease. The short term goal of the proposal is to develop statistical methods for age at onset data from population-based family studies of disease incidence. The methods for such studies must accommodate censoring, semi-parametric modeling and familial correlations. Further development is needed for methods which can model complex dependence structures and methods which can examine the fit of parametric dependence models to data. Accordingly, the specific aims of this proposal are development of: (1) a general strategy for evaluating the fit of parametric dependence models for familial clustering of ages at disease-onset; (2) a computationally simple method for genetic linkage analysis of age at onset data; (3) application and illustration of recently developed additive frailty models for complex familial dependence structures. Method (1) will be applied to a family study of cardiovascular disease and a twin study of appendectomy. Method (2) will be applied to ongoing genetic studies conducted at UCSF. Method (3) will be applied to a family study of coronary heart disease in Western Australia. Well-documented, user-friendly programs will be developed and made publicly available.
| Glidden, David V; Vittinghoff, Eric (2004) Modelling clustered survival data from multicentre clinical trials. Stat Med 23:369-88 |
| Zhong, Xiaoyun; Li, Hongzhe (2004) Score tests of genetic association in the presence of linkage based on the additive genetic gamma frailty model. Biostatistics 5:307-27 |
| Glidden, David V; Liang, Kung-Yee; Chiu, Yen-Feng et al. (2003) Multipoint affected sibpair linkage methods for localizing susceptibility genes of complex diseases. Genet Epidemiol 24:107-17 |
| Glidden, David V; Liang, Kung-Yee (2002) Ascertainment adjustment in complex diseases. Genet Epidemiol 23:201-8 |
| Glidden, David V (2002) Robust inference for event probabilities with non-Markov event data. Biometrics 58:361-8 |
