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Consistency of the Semi-parametric MLE under the Cox Model with Right-Censored Data


 
 We studied the consistency of the semi-parametric maximum likelihood estimator (SMLE) under the Cox regression model with right-censored (RC) data.
 
 
 
 Consistency proofs of the MLE are often based on the Shannon-Kolmogorov inequality, which requires finite E(lnL), where L is the likelihood function.
 
 
 
 The results of this study show that one property of the semi-parametric MLE (SMLE) is established.
 
 
 
 Under the Cox model with RC data, E(lnL) may not exist. We used the Kullback-Leibler information inequality in our proof.
