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...

Many papers have investigated how personal characteristics and environmental variables affect welfare durations of unmarried mothers. This paper estimates proportional hazard models for welfare durations that allow for either fixed state or fixed labor market area effects. Conditioning on residence location by fixed effects can limit the impact of three types of potential bias. (1) Estimates of...

This article concerns the statistical modelling of emergency service response times. We apply advanced methods from spatial survival analysis to deliver inference for data collected by the London Fire Brigade on response times to reported dwelling fires. Existing approaches to the analysis of these data have been mainly descriptive; we describe and demonstrate the advantages of a more sophistic...

This paper proposes a discrete-time hazard regression approach based on the relation between hazard rate models and excess over threshold models, which are frequently encountered in extreme value modelling. The proposed duration model employs a exible link function and incorporates the grouped-duration analogue of the wellknown Cox proportional hazards model and the proportional odds model as s...

Correlated survival times can be modelled by introducing a random effect, or frailty component, into the hazard function. For multivariate survival data we extend a non-PH model, the generalized time-dependent logistic survival model, to include random effects. The hierarchical-likelihood procedure, which obviates the need for marginalization over the random effect distribution, is derived for ...

We investigate the variable selection problem for Cox’s proportional hazards model, and propose a unified model selection and estimation procedure with desired theoretical properties and computational convenience. The new method is based on a penalized log partial likelihood with the adaptively-weighted L1 penalty on regression coefficients, and is named adaptive-LASSO (ALASSO) estimator. Inste...

Cox proportional hazards model is a commonly used model in providing hazard ratio to compare survival times of two population groups. The exponentiated linear regression part of the model describes the effects of explanatory variables on hazard ratio. PROC PHREG is a SAS procedure that implements the Cox model and provides the hazard ratio estimate. The estimate is interpreted as the percent ch...

Due to natural or artificial clustering, multivariate survival data often arise in biomedical studies, for example, a dental study involving multiple teeth from each subject. A certain proportion of subjects in the population who are not expected to experience the event of interest are considered to be "cured" or insusceptible. To model correlated or clustered failure time data incorporating a ...

First hitting time models are a technique of modeling a stochastic process as it approaches or avoids a boundary, also known as a threshold. The process itself may be unobservable, making this a difficult problem. Regression techniques, however, can be employed to model the data as it compares to the threshold, creating a class of first hitting time models called threshold regression models. Su...

We provide an overview of semiparametric models commonly used in survival analysis, including proportional hazards model, proportional odds models and linear transformation models. The applications of these models to different types of censored data, either univariate or multivariate survival analysis, are given. For each case, inference procedures using censored observations are discussed. & 2...