Abstract
Dropout is a problem faced by public and private universities. Therefore, the motivation of
this work is to investigate the characteristics of students enrolled in a regular undergraduate
course and verify which one is related with dropout and/or graduate. For the study we consider
competitive risk models, and we propose to use the transformation of complementary log-log
for the risk function into discrete data to study specific cause risk at a period of time (calculated
in semesters). For the parameters estimations we used Bayesian Inference. We verified that
the model proposed in this work can be adjusted to the theoretical data. In real data from the
Applied Mathematics course to the Institute of Mathematical and Computer Sciences (ICMC),
we concluded that parental education and admission type influence in dropout outcome