In this study, we consider a general, flexible, parametric hazard-based regression model for censored lifetime data with covariates and term it the “general hazard (GH)” model. Some well-known models, such as accelerated failure time (AFT), proportional (PH) well (AH) accounting crossed survival curves, are sub-classes of general proposed class covariate’s effect is identified having two distin...

The analysis of lifetime data is an important research area in statistics, particularly among econometricians and biostatisticians. The two most popular semi-parametric models are the proportional hazards model and the accelerated failure time (AFT) model. The proportional hazards model is computationally advantageous over virtually any other competing semi-parametric model because the ubiquito...

Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multif...

In this article we focus on time-to-event studies with a randomised treatment assignment that may be compromised by selective compliance. Contrary to most of the extensive literature on evaluation studies we do not consider the effect of the treatment on some average outcome but on the hazard rate. In time-to-event studies the treatment may vary over time. Another complication of duration data ...

Objective: Accelerated Failure Time (AFT) models are an useful alternative of Cox- PH model to determine the significant predictors affecting survival patients. This article aims prognostic factors hospitalized Gall Bladder Cancer patients in Rajiv Gandhi Institute and Research Center, New Delhi, India by applying AFT Models. To best our knowledge, this is first study be carried out identifying...

A semiparametric accelerated failure time (AFT) model is proposed to evaluate the effects of risk factors on the unbiased failure times for the target population given the observed length-biased data. The analysis of length-biased data is complicated by informative right censoring due to the biased sampling mechanism, and consequently the techniques for conventional survival analysis are not ap...

In this article we develop an Instrumental Variable estimation procedure that corrects for possible endogeneity of a variable in a duration model. We assume a Generalized Accelerated Failure Time (GAFT) model. This model is based on transforming the durations and assuming a distribution for these transformed durations. The GAFT model encompasses two competing approaches to duration data; the (M...

OBJECTIVE Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional ha...

SUMMARY In the presence of high-dimensional predictors, it is challenging to develop reliable regression models that can be used to accurately predict future outcomes. Further complications arise when the outcome of interest is an event time, which is often not fully observed due to censoring. In this article, we develop robust prediction models for event time outcomes by regularizing the Gehan...

The censored linear regression model, also referred to as the accelerated failure time (AFT) model when the logarithm of the survival time is used as the response variable, is widely seen as an alternative to the popular Cox model when the assumption of proportional hazards is questionable. Buckley and James [Linear regression with censored data, Biometrika 66 (1979) 429-436] extended the least...