A Multilevel Hazards Model for Hierarchically Clustered Data

Model Estimation and an Application to the Study of Child Survival in Northeast Brazil

by Narayan Sastry

Download eBook for Free

FormatFile SizeNotes
PDF file 1.6 MB

Use Adobe Acrobat Reader version 10 or higher for the best experience.

The author presents a multivariate proportional hazards model for data that are clustered at two hierarchical levels and applies it to the study of the covariates of child mortality in Northeast Brazil. The model provides corrected parameter estimates and standard errors — as well as estimates of intra-group correlation of survival times at both levels — with survey data collected via a hierarchically clustered sampling scheme, such as the data from Northeast Brazil that are analyzed in this paper. The model accounts for the hierarchical clustering in the data by including two random-effects or frailty-effects. The author assumes that the two random-effects are independent and that each follows the gamma distribution. The parameters of the hazard model and the mixing distributions are estimated using the expectation-maximization (EM) algorithm. The author uses the incomplete data log-likelihood function to calculate standard errors. The author's results indicate that family and community clustering effects in Northeast Brazil are fairly small in magnitude but are of importance because they alter parameter estimates and standard errors in a systematic pattern.

This report is part of the RAND Corporation draft series. The unrestricted draft was a product of the RAND Corporation from 1993 to 2003 that represented preliminary or prepublication versions of other more formal RAND products for distribution to appropriate external audiences. The draft could be considered similar to an academic discussion paper. Although unrestricted drafts had been approved for circulation, they were not usually formally edited or peer reviewed.

This research in the public interest was supported by RAND, using discretionary funds made possible by the generosity of RAND's donors, the fees earned on client-funded research, and independent research and development (IR&D) funds provided by the Department of Defense.

The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.