Mediation Analysis for Censored Survival Data Under an Accelerated Failure Time Model

Accelerated failure time models for censored survival data under referral bias.

The estimation of progression to liver cirrhosis and identifying its risk factors are often of epidemiological interest in hepatitis C natural history study. In most hepatitis C cohort studies, patients were usually recruited to the cohort with a referral bias because clinically the patients with more rapid disease progression were preferentially referred to liver clinics. A pair of correlated ...

Failure Process Modeling with Censored Data in Accelerated Life Tests

Manufacturers need to evaluate the reliability of their products in order to increase the customer satisfaction. Proper analysis of reliability also requires an effective study of the failure process of a product, especially its failure time. So, the Failure Process Modeling (FPM) plays a key role in the reliability analysis of the system that has been less focused on. This paper introduces a f...

Inferences on Median Failure Time for Censored Survival Data

failure process modeling with censored data in accelerated life tests

manufacturers need to evaluate the reliability of their products in order to increase the customer satisfaction. proper analysis of reliability also requires an effective study of the failure process of a product, especially its failure time. so, the failure process modeling (fpm) plays a key role in the reliability analysis of the system that has been less focused on. this paper introduces a f...

Jackknife Empirical Likelihood for the Accelerated Failure Time Model with Censored Data

Kendall and Gehan estimating functions are used to estimate the regression parameter in accelerated failure time (AFT) model with censored observations. The accelerated failure time model is the preferred survival analysis method because it maintains a consistent association between the covariate and the survival time. The jackknife empirical likelihood method is used because it overcomes compu...