Currently, for a variety of mechatronic systems and components, sufficient failure behaviour data are not available. Endurance tests at customer-specific operating conditions provide manufacturers with specific failure time data. However, they are timeconsuming and expensive. Findings gained through experiments are valid only for the applied test conditions and loads. On the other hand, develop...

We have developed a prognostic index model for survival data based on an ensemble of artificial neural networks that optimizes directly on the concordance index. Approximations of the c-index are avoided with the use of a genetic algorithm, which does not require gradient information. The model is compared with Cox proportional hazards (COX) and three support vector machine (SVM) models by Van ...

A survival analysis on a data set of 295 early breast cancer patients is performed in this study. A new proportional hazards model, hypertabastic model was applied in the survival analysis. We assume a proportional hazards model, and select two sets of risk factors for death and metastasis for breast cancer patients respectively by using standard variable selection methods. To evaluate the perf...

In occupational epidemiology, it is often possible to obtain repeated measurements of exposure from a sample of subjects (workers) who belong to exposure groups associated with different levels of exposure. Average exposures from a sample of workers can be assigned to all members of that group including those who are not sampled, leading to a group-based exposure assessment. We discuss how this...

The Cox proportional-hazards regression model has achieved widespread use in the analysis of time-to-event data with censoring and covariates. The covariates may change their values over time. This article discusses the use of such time-dependent covariates, which offer additional opportunities but must be used with caution. The interrelationships between the outcome and variable over time can ...

In some cancer clinical studies, researchers have interests to explore the risk factors associated with competing risk outcomes such as recurrence-free survival. We develop a novel recursive partitioning framework on competing risk data for both prognostic and predictive model constructions. We define specific splitting rules, pruning algorithm, and final tree selection algorithm for the compet...

Some failure time data come from a population that consists of some subjects who are susceptible to and others who are nonsusceptible to the event of interest. The data typically have heavy censoring at the end of the follow-up period, and a standard survival analysis would not always be appropriate. In such situations where there is good scientific or empirical evidence of a nonsusceptible pop...

The Cox proportional hazards regression model has been widely used in the analysis of survival/duration data. It is semiparametric because the model includes a baseline hazard function that is completely unspecified. We study here the statistical inference of the Cox model where some information about the baseline hazard function is available, but it still remains as an infinite dimensional nui...

The primary objective of this work was to investigate and compare the use of the Cox proportional hazards model and Aalen’s additive model in analysing survival data. Survival data from a study of 52 patients with advanced breast cancer was investigated using the Cox proportional hazards model. The model was optimized by examining different aspects by use of appropriate residual plots. Covariat...

Apolipoproteins are associated with survival among patients on hemodialysis (HD), but these associations might be influenced by dysfunctional (oxidized) high-density lipoprotein (HDL). We assessed associations among apolipoproteins and oxidized HDL, mortality and cardiovascular disease (CVD) events in patients on HD. This prospective observational study examined 412 patients on prevalent HD. Bl...