Cox Regression Models with Time-Varying Covariates Applied to Survival Success of Young Firms 1()

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 independent variables assumed to remain constant throughout t...

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Bibliographic Details
Published in:Journal of Economic and Social Studies (Online) 2013-10, Vol.3 (2), p.53
Main Authors: Anavatan, Aygul, Karaoz, Murat
Format: Article
Language:English
Subjects:
Confidence intervals
Economic models
Entrepreneurs
Estimates
Independent variables
Random variables
Survival analysis
University graduates
Online Access:Get full text
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Summary: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 independent variables assumed to remain constant throughout the observation period. Model can give biased results in cases which this assumption is violated. One of the methods used modelling the hazard ratio in the cases that the proportional hazard assumption is not met is to add a time-dependent variable showing the interaction between the predictor variable and a parametric function of time. In this study, we investigate the factors that affect the survival time of the firms and the time dependence of these factors using Cox regression considering time-varying variables. The firm data comes from Business Development Centers (ISGEM) which is a prominent business incubation center operating in Turkey. [PUBLICATION ABSTRACT]
ISSN:1986-8499
1986-8502