Comparing coefficients of nested nonlinear probability models
Comparing coefficients of nested nonlinear probability models
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DOI：
10.1177/1536867x1101100306
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发表时间：
2011-01-01
期刊：
影响因子：
4.8
通讯作者：
Holm, Anders
中科院分区：
文献类型：
--
作者：
Kohler, Ulrich;Karlson, Kristian Bernt;Holm, Anders
在最近的一系列文章中，Karlson、霍尔姆和Breen（Breen、Karlson和霍尔姆，2011，http://papers.ssrn.com/sol3/papers.cfm? Karlson和霍尔姆，2011，Research in Stratification and Social Mobility 29：221 237; Karlson，霍尔姆和Breen，2010，http://www.yale.edu/ciqle/Breen_Scaling %20effects.pdf）已经开发了一种用于比较两个嵌套非线性概率模型的估计系数的方法。在本文中，我们描述了这种方法和用户编写的程序khb，它实现了该方法。KHB方法是一种通用的分解方法，不受非线性模型中跨模型比较中出现的重新缩放或衰减偏倚的影响。它恢复了控制变量Z介导或解释X与非线性概率模型基础的潜在结果变量Y* 之间关系的程度。它还分解离散和连续变量的效应，应用于平均部分效应，并提供分析导出的统计检验。该方法可以推广到广义线性模型族中的其他模型。
In a series of recent articles, Karlson, Holm, and Breen (Breen, Karlson, and Holm, 2011, http://papers.ssrn.com/sol3/papers.cfm?abstractid=1730065; Karlson and Holm, 2011, Research in Stratification and Social Mobility 29: 221 237;.Karlson, Holm, and Breen, 2010, http://www.yale.edu/ciqle/Breen_Scaling %20effects.pdf) have developed a method for comparing the estimated coefficients of two nested nonlinear probability models. In this article, we describe this method and the user-written program khb, which implements the method. The KHB method is a general decomposition method that is unaffected by the resealing or attenuation bias that arises in cross-model comparisons in nonlinear models. It recovers the degree to which a control variable, Z, mediates or explains the relationship between X and a latent outcome variable, Y*, underlying the nonlinear probability model. It also decomposes effects of both discrete and continuous variables, applies to average partial effects, and provides analytically derived statistical tests. The method can be extended to other models in the generalized linear model family.