Objectives The Cox proportional hazards (PH) model is commonly used in randomised clinical trials (RCTs) to assess a treatment effect after adjusting for known prognostic factors. However, the Cox model requires that a covariate effect is constant over time. Violation of this assumption invalidates the simple Cox model. Various PH checks exist, some in the form of statistical tests and some emp...

RESEARCH DESIGN AND METHODSdFracture-related hospitalization was defined using International Classification of Diseases, 9th revision, codes (733.1–733.19, 733.93– 733.98, or 800–829). We calculated the incidence rate of fracture-related hospitalization by age and used Cox proportional hazards models to investigate the association of diabetes with risk of fracture after adjustment for demograph...

When fitting the Cox proportional hazards model with missing covariates, it is inefficient to exclude observations with missing values in the analysis. Furthermore, if the missing-data mechanism is not Missing Completely At Random (MCAR), it may lead to biased parameter estimation. Many approaches have been suggested to handle the Cox proportional hazards model when covariates are sometimes mis...

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...

Cox proportional hazards model is a widely used method to analyse time-to-event data for survival analysis. In the medical field, age is the most common confounder of any association between risk factor and disease since most risk factors and the risk of disease change with age. Usually, age recorded at the start of the study (age-at-baseline) will be adjusted for in the model to account for th...

This paper uses the Cox proportional hazards model to analyze recent Broadway show data to investigate the factors that relate to the longevity of shows The type of show whether a show is a revival and rst week attendance for the show are predictive for longevity Favorable critic re views in the Daily News are related to greater success but reviews in The New York Times are not Winning major To...

This paper studies Cox‘s proportional hazards model under covariate measurement error. Nakamura‘s (1990) methodology of corrected log-likelihood will be applied to the so called Breslow likelihood, which is, in the absence of measurement error, equivalent to partial likelihood. For a general error model with possibly heteroscedastic and non-normal additive measurement error, corrected estimator...

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...

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 ...

Methods We evaluated 153 patients (28males) diagnosed younger than 20 years old, managed during 1980 through 2013 (median 7.0 years of duration). Good or poor outcome (persistence or recurrence) was analyzed in 126 patients followed for at least 12 months. Predictors for recurrence were analyzed among 108 pediatric PTC patients. Adult PTC patients (n = 3093) were finally included in Cox proport...