Last Updated: 04/06/07
Genomic Control for Association Studies under Various Genetic Models
Case-control studies are commonly used to study whether a candidate allele and a disease are associated. However, spurious association can arise due to population substructure or cryptic relatedness, which cause the variance of the trend test to increase. A novel genomic control approach had been developed to estimate the “variance inflation factor” using an additive genetic model. Dr. Freidlin and collaborators expand this approach to recessive and dominant genetic models. They also discuss appropriate uses for their method and the one derived for the additive model.
Zheng G, Freidlin B, Li ZH, Gastwirth GL. Genomic control for association studies under various genetic models. Biometrics 2005:61;187–93.
The case-cohort design is an efficient and economical design to study risk factors for infrequent disease in a large cohort. It involves the collection of covariate data from all failures ascertained throughout the entire cohort, and from the members of a random subcohort selected at the onset of follow-up. Dr. Shih develops case-cohort designs adapted to multivariate failure time data.
Lu S, Shih JH. Case-cohort designs and analysis of clustered failure time data. Biometrics (In press).
Dr. Shih also considered the problem of estimating covariate effects in the marginal Cox proportional hazard model and multilevel associations for child mortality data collected from a vitamin A supplementation trial in Nepal (Nepal Nutrition Intervention Project–Sarlahi, or NNIPS), where the data are clustered within households and villages. For this purpose, a class of multivariate survival models that can be represented by a function of marginal survival functions and accounts for hierarchical structure of clustering is exploited. Based on this class of models, an estimation strategy involving a within-cluster resampling procedure is proposed. The asymptotic theory for the proposed estimators is established, and the simulation study shows that the estimates are consistent. The analysis of the NNIPS study data shows that the association of mortality is much greater within households than within villages.
Shih JH, Lu S. Analysis of failure time data with multi-level clustering, with application to the child vitamin A supplementation trial in Nepal. Revision submitted to Biometrics.
