Time dependent COX regression: An application on survival success of young firms

The most widely used model in multivariate analysis of survival data is proportional hazards model proposed by Cox. While it is easy to get and interpret the results of the model, the basic assumption of proportional hazards model is that the hazard ratio obtained from the variable thought to have an effect on survival time is constant throughout the observation period. Model can give biased results in cases which this assumption is violated. One of the methods used to model the hazard ratio in the cases that the proportional hazard assumption is not met is that to add a time-dependent variable showing the interaction between the predictor variable and a parametric function of time. In this study, it is tried to determine the factors that affect the survival time of the firms are included in Business Development Centers (İŞGEM) which is one of the practices of an important business incubators operating in Turkey. The data set used in this study has been obtained from the TÜBİTAK project on ?The Factors Affecting Survival and Growth Performance of Newly Established Enterprises in Business Incubators: A Survey on the KOSGEB Business Development Centers (İŞGEM)?.