Author(s)

Yemane Hailu Fissuh^1,2*, Tsegay Giday Woldu³, Idriss Abdelmajid Idriss Ahmed¹, Abebe Zewdie Kebebe⁴

¹Department of Statistics, College of Applied Sciences, Beijing University of Technology, Beijing, China.
²Department of Statistics, College of Natural and Computational Sciences, Aksum University, Aksum, Ethiopia.
³Department of Mathematics, College of Applied Sciences, Beijing University of Technology, Beijing, China.
⁴School of Software Engineering, Faculty of Information Technology, Beijing University of Technology, Beijing, China.

The consideration of the time-varying covariate and time-varying coefficient effect in survival models are plausible and robust techniques. Such kind of analysis can be carried out with a general class of semiparametric transformation models. The aim of this article is to develop modified estimating equations under semiparametric transformation models of survival time with time-varying coefficient effect and time-varying continuous covariates. For this, it is important to organize the data in a counting process style and transform the time with standard transformation classes which shall be applied in this article. In the situation when the effect of coefficient and covariates change over time, the widely used maximum likelihood estimation method becomes more complex and burdensome in estimating consistent estimates. To overcome this problem, alternatively, the modified estimating equations were applied to estimate the unknown parameters and unspecified monotone transformation functions. The estimating equations were modified to incorporate the time-varying effect in both coefficient and covariates. The performance of the proposed methods is tested through a simulation study. To sum up the study, the effect of possibly time-varying covariates and time-varying coefficients was evaluated in some special cases of semiparametric transformation models. Finally, the results have shown that the role of the time-varying covariate in the semiparametric transformation models was plausible and credible.

Estimating Equation, Semiparametric Transformation Models, Time-to-Event Outcomes, Time-Varying Coefficients, Time-Varying Covariate

Fissuh, Y. , Woldu, T. , Ahmed, I. and Kebebe, A. (2019) A Simulation Study on Comparing General Class of Semiparametric Transformation Models for Survival Outcome with Time-Varying Coefficients and Covariates. Open Journal of Statistics, 9, 169-180. doi: 10.4236/ojs.2019.92013.