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Analysis of Survival Data with Multiple Causes of Failure

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Abstract

The purpose of the paper is to compare results of estimation and inference concerning covariate effects as obtained from two approaches to the analysis of survival data with multiple causes of failure. The first approach involves a dynamic model for the cause-specific hazard rate. The second is based on a static logistic regression model for the conditional probability of having had an event of interest. The influence of sociodemographic characteristics on the rate of family initiation and, more importantly, on the choice between marriage and cohabitation as a first union, is examined. We found that results, generally, are similar across the methods considered. Some issues in relation to censoring mechanisms and independence among causes of failure are discussed.

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Ghilagaber, G. Analysis of Survival Data with Multiple Causes of Failure. Quality & Quantity 32, 297–324 (1998). https://doi.org/10.1023/A:1004312403022

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