BACKGROUND Regression models for survival data have traditionally been based on the Cox regression model. However, its validity relies heavily on assumption of proportional hazards. Another restriction of the Cox model is insufficiency in dealing with time-varying covariate effects, since the regression coefficients are assumed constant. These weaknesses have generated interest in alternative a...

background and purpose: the goal of this study is application of the proportional hazards model (ph) and accelerated failure time model (aft), with consideration weibull distribution, to determine the level of effectiveness of the factors affecting on the level of disease-free survival (dfs) of the patients with breast cancer. materials and methods: based on the retrospective descriptive studie...

The life cycle cost of a system is influenced by its maintainability. Maintainability is a design parameter, whose operational conditions can affect it significantly. Hence, the effects of these operational conditions should be quantified early in the design phase. The proportional repair model (PRM), which is developed based on the proportional hazard model (PHM), can be used to analyze mainta...

conclusions the use of smoothing methods helps us to eliminate non-linear effects but it is more appropriate to use cox proportional hazards model in medical data because of its’ ease of interpretation and capability of modeling both continuous and discrete covariates. also, cox proportional hazards model and smoothing methods analysis identified that age at diagnosis and tumor size were indepe...