A family of tests for the presence of regression effect under proportional and non-proportional hazards models is described. The non-proportional hazards model, although not completely general, is very broad and includes a large number of possibilities. In the absence of restrictions, the regression coefficient,   t  , can be any real function of time. When   , t    we recover the propo...

We propose a new method for variable selection and estimation in Cox's proportional hazards model. Our proposal minimizes the log partial likelihood subject to the sum of the absolute values of the parameters being bounded by a constant. Because of the nature of this constraint it tends to produce some coeecients that are exactly zero and hence gives interpretable models. The method is a variat...

Results. Of the 18,602 identified patients, there was a 5.2% Study Design. Retrospective review of a prospective cohort. Objective. The aim of the study was to determine the patient characteristics and surgical procedure factors related to increased rates of 30-day unplanned readmission and major perioperative complications after spinal fusion surgery, and the association between unplanned read...

For the final reduced multivariate Cox proportional hazards model presented in Table 3 of the main text, we assessed the proportional hazards assumption via the Schoenfeld residuals. We examined plots of the residuals for each variable against time to check for a non-­‐zero slope, which indicates that the proportional hazards assumption is violated (Hosmer et al. 1999). We then performed statis...

This article investigates the value of perfect monitoring information for optimal replacement of deteriorating systems in the Proportional Hazards Model (PHM). A continuous-time Markov chain describes the condition of the system. Although the form of an optimal replacement policy for system under periodic monitoring in the PHM was developed previously, an approximation of the Markov process as ...

Choose the Cox proportional hazards regression model if the values in your dependent variable are duration observations. The advantage of the semi-parametric Cox proportional hazards model over fully parametric models such as the exponential or Weibull models is that it makes no assumptions about the shape of the baseline hazard. The model only requires the proportional hazards assumption that ...

We study application of the Exponential Tilt Model (ETM) to compare survival distributions in two groups. The ETM assumes a parametric form for the density ratio of the two distributions. It accommodates a broad array of parametric models such as the log-normal and gamma models and can be sufficiently flexible to allow for crossing hazard and crossing survival functions. We develop a nonparamet...

Bayesian bootstrap was proposed by Rubin (1981) and its theoretical properties and application to survival models without covariates was studies by Lo (1993) and others. Bayesian bootstrap, empirical likelihood and bootstrap are diierent approaches based on the same idea, approximating the nonparametric model with the family of distributions whose supports are the set of observations. Based on ...

Choose the Cox proportional hazards regression model if the values in your dependent variable are duration observations. The advantage of the semi-parametric Cox proportional hazards model over fully parametric models such as the exponential or Weibull models is that it makes no assumptions about the shape of the baseline hazard. The model only requires the proportional hazards assumption that ...

Background and Purpose: The strength of the association between blood pressure and stroke incidence is dependent on the number of blood pressure measurements. Different summary variables of repeated blood pressure measurements taken during 10 years were evaluated in relation to the long-term risk of stroke in the Zutphen Study. Methods: During the period 1960-1970 repeated blood pressure measur...