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Statistical analysis and application of competing risks model with regression

Petr Volf ; Institute of Information Theory and Automation, Prague, Czech Republic

Puni tekst: engleski pdf 322 Kb

str. 13-21

preuzimanja: 630



The paper deals with the methods of statistical analysis of
dependent competing risks in the presence of covariates. The
problem of identification of marginal and joint distributions of
competing random variables is recalled and certain identifiability
results in the framework of regression models are
presented. The main objective is then to study the case when the
correlation of competing variables depends on covariates, as this
phenomenon has not been taken into account in the most of papers
dealing with the identifiability of competing risks models with
regression. Such a dependence is demonstrated and estimated on a
real example with unemployment data.

Ključne riječi

competing risks; copula; Cox's regression; survival analysis; unemployment

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