International Journal of Applied Research
Vol. 1, Issue 9, Part N (2015)
Expected the Survival Life Time for heart Patients by using Cox regression model
Cox regression model is one of the models can be used in analyzing survival data and we can detect relationship between the explanatory variables and their survival time, so the cox regression is semi parametric model that consist two parts, the first part is nonparametric (λ0(t)) and other is parametric part (e(βź )) where (β́ ) is the vector of unknown parameters, (z) is the vector of explanatory variable. The data which used in this study is type one of censoring was taken from heart center with left-censored data, testing distribution of survival time by using goodness of test and we find the distribution of survival time is unknown. Selecting cox regression model as the best model to analysis data by checking the assumption Cox regression model once graphically by using Kaplan–Meier estimator to estimating the survival function from lifetime data of patients, We estimated the parameters by using (partial likelihood) method and test the model parameter by using (Wald) test which shown that only two parameters (?) are effect on survival time.
How to cite this article:
Monem AM, Shao T. Expected the Survival Life Time for heart Patients by using Cox regression model. Int J Appl Res 2015;1(9):883-889.