Analysis of failure time data with multilevel clustering, with application to the child vitamin a intervention trial in Nepal.

Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland 20892, USA. jshih@mail.nih.gov

We consider 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, where the data are clustered within households and villages. For this purpose, a class of multivariate survival models that can be represented by a functional 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, and a model assessment approach is presented. The asymptotic theory for the proposed estimators and lack-of-fit test is established. The simulation study shows that the estimates are approximately unbiased, and the proposed test statistic is conservative under extremely heavy censoring but approaches the size otherwise. The analysis of the Nepal study data shows that the association of mortality is much greater within households than within villages.

PMID: 17825001 [PubMed - indexed for MEDLINE]