基于加速威布尔回归模型的新型冠状病毒感染发生率影响因素研究

Husam Yaseen, Raya Salim Al Rassam
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引用次数: 0

摘要

威布尔回归模型是最重要的参数回归模型之一。由于知道响应变量服从威布尔分布的概率分布,这使得基于基线危害函数估计回归参数成为可能。利用极大似然估计法对威布尔分布的参数进行估计。R软件用于估计回归系数和识别模拟结果的最重要特征。在本文中,我们调查了影响摩苏尔市Al-Shiffa医院冠状病毒患者进展的因素。此外,本研究的重点是病情危重的患者,其病例需要在人工呼吸机持续气道正压通气(CPAP)下住院期间进行监测。将这6个变量作为对损伤病例影响最大的变量,采用一定的统计标准发现影响最大的变量是Remdesivir和O2。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study of the Factors Affecting the Incidence of COVID-19 Infection Using an Accelerrated Weibull Regression Model
The Weibull regression model is one of the most important parametric regression models. Because of the knowledge of the probability distribution of the response variable following the Weibull distribution, which facilities the possibility of estimating the regression parameters based on the baseline hazard function. It is estimated by estimating the parameters of the Weibull distribution using the maximum likelihood estimation method. The R software was used for the purpose of estimating the regression coefficients and identifying the most significant features that model the outcome. In this paper, we investigate the factors affecting the progression of Corona virus patients from Al-Shiffa Hospital in the city of Mosul. In addition, this study focused on patients who were in a critical condition, and whose cases necessitated their monitoring during their stay under the artificial respiration machine Continues Positive Airway Pressure (CPAP). The six variables were taken as the most influential on the injury case and it was found that the most influential variables were Remdesivir and O2 using some statistical criteria.
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