background: precise diagnosis of disease risk factors via efficient statistical models is the primary step for reducing the heavy costs of breast cancer, as one of the most highly prevalent cancer throughout the world. therefore, the aim of this study was to present a recently introduced statistical model in order to assess its proficiency for model fitting. methods: the information of 1465 eli...

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...

background: in survival studies when the event times are dependent, performing of the analysis by using of methods based on independent assumption, leads to biased. in this paper, using copula function and considering the dependence structure between the event times, a parametric joint distribution has made fitting to the events, and the effective factors on each of these events would be determ...

Nowadays, one of the most important topics in risk management of banks, financial, and credit institutions is credit risk management. In this research, the researchers used survival analytic methods for credit risk modeling in terms of the conditional distribution function of default time. As a practical task, the authors considered the reward credit portfolio of Tose'e Ta'avon Bank of Guilan P...

Background: Thalassemia major (TM) is a severe disease and the most common anemia worldwide. The survival time of the disease and its risk factors are of importance for physicians. The present study was conducted to apply the semi-parametric Cox PH model and use parametric proportional hazards (PH) and accelerated failure time (AFT) models to identify the risk factors related to survival of TM ...