‘Modeling and Analysis of Competing Risks Data’


Autoria(s): Sreedevi, E P; Dr.Sankaran, P G
Data(s)

23/05/2014

23/05/2014

09/04/2010

Resumo

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.

Department of Statistics, Cochin University of Science and Technology

Cochin University of Science and Technology

Identificador

http://dyuthi.cusat.ac.in/purl/3810

Idioma(s)

en

Publicador

Cochin University Of Science And Technology

Palavras-Chave #Censoring #Truncation #Competing Risks Models #Neural Network Models for Competing Risks Data #Tests for Continuous Lifetime Data
Tipo

Thesis