نتایج جستجو برای: Cox Hazard Function
تعداد نتایج: 1301063 فیلتر نتایج به سال:
Background: The occupational exposure conditions such as dust concentration, exposure time, smoking status and use of respiratory protection device are effective on pulmonary function disorder. The aim of this study was to determine the risk of pulmonary function disorder in the workers exposed to silica dust in the stone crushing by using Cox regression model. Method: 117 of workers employ...
the waiting time between children births are called tempo. this phenomenon plays a crucial role in the child and mother health. the purpose of the present study is determination of factors which influence this variable of interest. a significance level of 5% and power of 80% considered to calculate the required sample size for this cross sectional study. the sample size of 124 women determined ...
objective: tempo is the average waiting time to next birth for a woman. role of fertility as the most important phenomenon determining population fluctuations due to the studies of it compared with other demographic phenomena be important and review the multifarious socioeconomic factors of it share a large effective population studies. general purpose of this study is fitting the cox model to...
in this paper, the cox proportional hazard model is used to answer several questions. in general, fourteen variables are applied in four groups: firm, industry, expenditure human resources specific characteristics as well. according to the previous literature in this field, the findings of this paper also show that the factors which affect life duration of firms are different between industries...
Abstract Background and purpose: Coronary artery disease is one of the major causes of death worldwide and analysis of survival data is important in these patients. The Cox model not only calculates the hazard function but also introduces other significant variables. Materials and methods: 128 patients referred to Mazandaran Heart Center from 2005 to 2007 and treated by angioplasty were fol...
By existing censor and skewness in survival data, some models such as weibull are used to analyzing survival data. In addition, parametric and semiparametric models can be obtained from baseline hazard function of Cox model to fit to survival data. However these models are popular because of their simple usage but do not consider unknown risk factors, that's why cannot introduce the be...
Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...
cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. in recent decades, artificial neural network model has been increasingly applied to predict survival data. this research was conducted to compare cox regression and artificial neural network models in prediction of kidney transplant survival. the prese...
Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...
Background and Aim: In many diagnostic studies, including surveying the survival of patients with gastric cancer where each individual after surgery can experience more than one type of event, and the occurrence of one type of event hinders the occurrence of other types of events, the question of competing risk is raised. For checking the effect of each covariate on the occurrence of any even...
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