A nested frailty model for survival data, with an application to the study of child survival in Northeast Brazil
The author presents a multivariate proportional hazards model for data that are clustered at two hierarchical levels. The model provides corrected parameter estimates and standard errors, as well as estimates of intra-group correlation at both levels. The model is estimated using the expectation-maximization (EM) algorithm. The author applies the model to an analysis of the covariates of child survival using survey data from northeast Brazil collected via a hierarchically clustered sampling scheme. She finds that family and community frailty effects are fairly small in magnitude but are of importance because they alter the results in a systematic pattern.