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Please use this identifier to cite or link to this item: http://purl.org/purl/3810

Title: ‘Modeling and Analysis of Competing Risks Data’
Authors: Sreedevi, E P
Dr.Sankaran, P G
Keywords: Censoring
Truncation
Competing Risks Models
Neural Network Models for Competing Risks Data
Tests for Continuous Lifetime Data
Issue Date: 9-Apr-2010
Publisher: Cochin University Of Science And Technology
Abstract: there has been much research on analyzing various forms of competing risks data. Nevertheless, there are several occasions in survival studies, where the existing models and methodologies are inadequate for the analysis competing risks data. ldentifiabilty problem and various types of and censoring induce more complications in the analysis of competing risks data than in classical survival analysis. Parametric models are not adequate for the analysis of competing risks data since the assumptions about the underlying lifetime distributions may not hold well. Motivated by this, in the present study. we develop some new inference procedures, which are completely distribution free for the analysis of competing risks data.
Description: Department of Statistics, Cochin University of Science and Technology
URI: http://dyuthi.cusat.ac.in/purl/3810
Appears in Collections:Faculty of Sciences

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