Resumen de Facing incomplete data due to the double truncation scheme

Jacobo de Uña Álvarez , Carla María Gonçalves de Macedo Moreira

• One important reason for specialized statistical models and methods for survival time is the need to accommodate some of the items of the sample by the previous occurrence of some other event called a loss. There are various types of losses that lead to incomplete data, i.e., grouping, censoring and/or truncation. Truncated data appear in a number of elds including Astronomy, Economics and Survival Analysis. The statistical methods were deeply investigated in the eighties and early nineties, for situations involving left-truncated data; however, for two-sided truncation the literature is much scarcer. In this paper we present some statistical methods involving doubly truncated data in various elds. The application of the referred techniques to real data is also included.