gastric cancer is the most prevalent cancer among men and the third most prevalent cancer among women in iran. its most important reason for death is its belated diagnosis at the advanced stages of the disease. various factors can be effective on the survival of these patients after surgery, which are the major concern in this study.data from 330 patients with gastric cancer who had undergone s...

conclusions by controlling the modifiable risk factors and modality of treatment in our study, physicians can reach more effective treatment. results at the end of the study, long-term graft failure was seen in 27 (10.2%) cases. one-year and 2-year graft survival after diagnosis of cancer were 93.6% and 91.7%, respectively. the univariate analysis showed that the incidence of chronic graft loss...

This article addresses a connection between the Bradley and Terry (1952A) model and Cox (1972) proportional hazards model. We show that the partial likelihood of random variables that satisfy the stratified proportional hazards assumption of Cox (1972) coincides with the likelihood given by the Bradley-Terry (BT) model for rank order events. Such a connection not only allows many available soft...

BACKGROUND Smoothing methods are widely used to analyze epidemiologic data, particularly in the area of environmental health where non-linear relationships are not uncommon. This study focused on three different smoothing methods in Cox models: penalized splines, restricted cubic splines and fractional polynomials. OBJECTIVES The aim of this study was to assess the effects of prognostic facto...

Introduction: Neuropathy is a common complication of diabetes that can cause disability in diabetic patients. The aim of this study was to determine of affective factors in the Event Time of Neuropathy in type 2 diabetes using Cox proportional hazards model. Materials and Methods: This study included 371 patients with type II diabetes without neuropathy who were registered at Fereydunshahr diab...

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...

The objective of hazards (lifetime) analysis is to advance and promote statistical science in the various applied fields that deal with lifetime (survival) data including: actuarial science and reliability engineering. The lifetime data analysis provides special techniques that are required to compare the risks for failure. Bayesian semi-parametric methods have been applied to survival analysis...