Multinomial logistic regression (MNL) is an attractive statistical approach in modeling the vehicle crash severity as it does not require the assumption of normality, linearity, or homoscedasticity compared to other a...Multinomial logistic regression (MNL) is an attractive statistical approach in modeling the vehicle crash severity as it does not require the assumption of normality, linearity, or homoscedasticity compared to other approaches, such as the discriminant analysis which requires these assumptions to be met. Moreover, it produces sound estimates by changing the probability range between 0.0 and 1.0 to log odds ranging from negative infinity to positive infinity, as it applies transformation of the dependent variable to a continuous variable. The estimates are asymptotically consistent with the requirements of the nonlinear regression process. The results of MNL can be interpreted by both the regression coefficient estimates and/or the odd ratios (the exponentiated coefficients) as well. In addition, the MNL can be used to improve the fitted model by comparing the full model that includes all predictors to a chosen restricted model by excluding the non-significant predictors. As such, this paper presents a detailed step by step overview of incorporating the MNL in crash severity modeling, using vehicle crash data of the Interstate I70 in the State of Missouri, USA for the years (2013-2015).展开更多
诊断准确性试验(diagnostic test accuracy,DTA)的灵敏度与特异度之间存在固有的负相关性,为避免二者间负相关性对诊断试验结果的评价产生影响,很多学者提出了双变量模型,因其保留了原始数据的二维结构特性,双变量模型通过参数拟合可以...诊断准确性试验(diagnostic test accuracy,DTA)的灵敏度与特异度之间存在固有的负相关性,为避免二者间负相关性对诊断试验结果的评价产生影响,很多学者提出了双变量模型,因其保留了原始数据的二维结构特性,双变量模型通过参数拟合可以得到灵敏度和特异度的综合估计量值及二者之间负相关的值,从而对诊断试验的准确性进行综合性分析。当前最具代表的是由Reitsma等提出的线性混合双变量模型,Metatron程序包正是基于此模型所研发的用于DTA Meta分析的程序包,同时本文将对R软件中专用于DTA Meta分析的程序包做出比较,便于使用者选择。展开更多
文摘Multinomial logistic regression (MNL) is an attractive statistical approach in modeling the vehicle crash severity as it does not require the assumption of normality, linearity, or homoscedasticity compared to other approaches, such as the discriminant analysis which requires these assumptions to be met. Moreover, it produces sound estimates by changing the probability range between 0.0 and 1.0 to log odds ranging from negative infinity to positive infinity, as it applies transformation of the dependent variable to a continuous variable. The estimates are asymptotically consistent with the requirements of the nonlinear regression process. The results of MNL can be interpreted by both the regression coefficient estimates and/or the odd ratios (the exponentiated coefficients) as well. In addition, the MNL can be used to improve the fitted model by comparing the full model that includes all predictors to a chosen restricted model by excluding the non-significant predictors. As such, this paper presents a detailed step by step overview of incorporating the MNL in crash severity modeling, using vehicle crash data of the Interstate I70 in the State of Missouri, USA for the years (2013-2015).
文摘诊断准确性试验(diagnostic test accuracy,DTA)的灵敏度与特异度之间存在固有的负相关性,为避免二者间负相关性对诊断试验结果的评价产生影响,很多学者提出了双变量模型,因其保留了原始数据的二维结构特性,双变量模型通过参数拟合可以得到灵敏度和特异度的综合估计量值及二者之间负相关的值,从而对诊断试验的准确性进行综合性分析。当前最具代表的是由Reitsma等提出的线性混合双变量模型,Metatron程序包正是基于此模型所研发的用于DTA Meta分析的程序包,同时本文将对R软件中专用于DTA Meta分析的程序包做出比较,便于使用者选择。
