Um modelo de risco proporcional dependente do tempo

Abstract

Survival data analysis models is used to study experimental data where, normally, the variable "answer"is the time passed until an event of interest. Many authors do prefer modeling survival data, in the presence of co-variables, by using a hazard function - which is related with its interpretation. The Cox model (1972) - most commonly used by the authors - is applicable when the fail rates are proportional. This model is very flexible and used in the survival analysis. It can be easily extended to, for example, incorporate the time-dependent co-variables. In the present work we propose a proportional risk model which incorporates a time-dependent parameter named "time-dependent proportional risk model".