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...

Knowledge of factors that affect the under-five year child mortality is important because it pertains to policy and programs. Causes and differences of under-five mortality between rural and urban area help decision makers to assess programmatic needs and prioritize interventions. This paper investigates the causes and differences of under-five mortality between rural and urban area in Banglade...

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 ...

Survival regression is used to estimate the relation between time-to-event and feature variables, important in application domains such as medicine, marketing, risk management, sales management. Nonlinear tree based machine learning algorithms implemented libraries XGBoost, scikit-learn, LightGBM, CatBoost are often more accurate practice than linear models. However, existing state-of-the-art i...

The goals of this study were to determine if the muscle contributions to vertical and fore-aft acceleration of the mass center differ between crouch gait and unimpaired gait and if these muscle contributions change with crouch severity. Examining muscle contributions to mass center acceleration provides insight into the roles of individual muscles during gait and can provide guidance for treatm...

Accelerated failure time (AFT) models are useful regression tools to study the association between a survival time and covariates. Semiparametric inference procedures have been proposed in an extensive literature. Among them, Fygenson and Ritov (1994) proposed an estimating equation which is monotone in the regression parameter and has some excellent properties. However, there exists a serious ...

The reliability data is getting used to monitor and improve the quality of products or services. Nowadays, most of products or services are the results of processes with dependent stages referred to as multi-stage process. In these processes, the quality characteristics are affected by the quality characteristics in the previous stages, called as cascade property. In some cases, it is not possi...

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...

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...

Considering the progression of ESRD—left untreated and in the context of maintenance hemodialysis—there can be little doubt that the delivered dose of hemodialysis impacts patient survival. What remains at issue is how best to operationally define hemodialysis dose, a necessary precondition to defining the dose that represents “enough” dialysis. Presently, hemodialysis dose is most often measur...