A0733
Title: Additive time-dependent hazard model with doubly truncated data
Authors: Gordon Frank - University of Rostock (Germany) [presenting]
Minwoo Chae - The University of Texas at Austin (United States)
Yongdai Kim - Seoul National University (Korea, South)
Abstract: For doubly truncated data, i.e. the variables of interest are only observable if they lie in a certain random interval, an additive hazard model with time-dependent regression coefficients is investigated. Consistency and asymptotic normality are proven under mild assumptions. A simulation study investigates the finite sample properties and the influence of the truncation distribution on the estimation error. Finally, the method is applied to a doubly truncated data set of German companies, where the age at insolvency is of interest.
