Computing measures of explained variation for logistic regression models
Computing measures of explained variation for logistic regression models
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DOI：
10.1016/s0169-2607(98)00061-3
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发表时间：
1999-01-01
影响因子：
6.1
通讯作者：
Schemper, M
中科院分区：
文献类型：
--
作者：
Mittlböck, M;Schemper, M
解释变异的比例（R-2）经常用于一般线性模型，但在逻辑回归中没有R-2的标准定义。我们提出了一个SAS宏计算两个R-2-措施的基础上皮尔逊和偏差残差的逻辑回归。此外，调整后的版本，这两种措施，应防止通货膨胀的R-2在小样本。(C)1999爱思唯尔科学爱尔兰有限公司保留所有权利。
The proportion of explained variation (R-2) is frequently used in the general linear model but in logistic regression no standard definition of R-2 exists. We present a SAS macro which calculates two R-2-measures based on Pearson and on deviance residuals for logistic regression. Also, adjusted versions for both measures are given, which should prevent the inflation of R-2 in small samples. (C) 1999 Elsevier Science Ireland Ltd. All rights reserved.