Copula bivariate probit models: with an application to medical expenditures.
Copula bivariate probit models: with an application to medical expenditures.
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Copula 双变量概率模型：在医疗支出中的应用。
DOI：
10.1002/hec.1801
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发表时间：
2012
期刊：
影响因子：
2.1
通讯作者：
R. Winkelmann
中科院分区：
文献类型：
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作者：
R. Winkelmann
双变量概率模型经常用于估计内源二元回归量（“治疗”）对二元健康结果变量的影响。本文讨论了简单的修改，这些修改维持边际分布的概率假设，同时使用联结函数引入非正态依赖性。在将 copula 双变量概率模型应用于保险状况对缺乏流动医疗保健支出的影响时，基于 Frank copula 的模型优于标准双变量概率模型。
The bivariate probit model is frequently used for estimating the effect of an endogenous binary regressor (the 'treatment') on a binary health outcome variable. This paper discusses simple modifications that maintain the probit assumption for the marginal distributions while introducing non-normal dependence using copulas. In an application of the copula bivariate probit model to the effect of insurance status on the absence of ambulatory health care expenditure, a model based on the Frank copula outperforms the standard bivariate probit model.