Nonparametric estimation of a dependent competing risks model for unemployment durations

Parametric Estimation in a Recurrent Competing Risks Model

A resource-efficient approach to making inferences about the distributional properties of the failure times in a competing risks setting is presented. Efficiency is gained by observing recurrences of the compet- ing risks over a random monitoring period. The resulting model is called the recurrent competing risks model (RCRM) and is coupled with two repair strategies whenever the system fails. ...

Penalized Splines - Estimation with Longitudinal Unemployment Data Analyses of Unemployment Durations and Unemployment Risks in Germany

References 93 VI 1 Introduction Unemployment is still a central problem in European economies and an abiding theme in labour market policy. In the 1990s, in the European Union, rising unemployment led to an European employment policy and a new section on employment was introduced into the Amsterdam Treaty signed in October 1997. In the same year, the European Employment Strategy (EES) was initi...

A copula model for dependent competing risks

Many popular estimators for duration models require independent competing risks or independent censoring. In contrast, copula based estimators are also consistent in presence of dependent competing risks. In this paper we suggest a computationally convenient extension of the Copula Graphic Estimator (Zheng and Klein, 1995) to a model with more than two dependent competing risks. We analyse the ...

Nonparametric Estimation for Current Status Data with Competing Risks

Nonparametric estimation with left truncated semi-competing risks data

SUMMARY Cause-specific hazard and cumulative incidence function are of practical importance in competing risks studies. Inferential procedures for these quantities are well developed and can be applied to semi-competing risks data, where a terminating event censors a non-terminating event, after coercing the data into the competing risks format. Complications arise when there is left truncation...