A unifying switching regime regression framework with applications in health economics
A unifying switching regime regression framework with applications in health economics
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DOI：
10.1080/07474938.2023.2255438
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发表时间：
2023-10
影响因子：
1.2
通讯作者：
G. Marra;Rosalba Radice;David Zimmer
中科院分区：
文献类型：
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作者：
G. Marra;Rosalba Radice;David Zimmer
摘要受三个健康经济学相关案例研究的启发，我们提出了一个统一和灵活的回归建模框架，涉及政权切换。该建议可以处理所考虑的结果通过一个巨大的范围内的边缘分布的特殊的分布形状，允许各种各样的Copula依赖结构，并允许指定所有的模型参数（包括依赖参数）作为灵活的函数的协变量效应。该算法是基于一个计算效率高，稳定的惩罚最大似然估计方法。建议的建模框架在卫生经济学的三个应用中，使用的数据从医疗支出面板调查，发现新的模式。该框架已被纳入R软件包GJRM，从而使用户能够适合所需的模型，并产生易于解释的数字和视觉摘要。
Abstract Motivated by three health economics-related case studies, we propose a unifying and flexible regression modeling framework that involves regime switching. The proposal can handle the peculiar distributional shapes of the considered outcomes via a vast range of marginal distributions, allows for a wide variety of copula dependence structures and permits to specify all model parameters (including the dependence parameters) as flexible functions of covariate effects. The algorithm is based on a computationally efficient and stable penalized maximum likelihood estimation approach. The proposed modeling framework is employed in three applications in health economics, that use data from the Medical Expenditure Panel Survey, where novel patterns are uncovered. The framework has been incorporated in the R package GJRM, hence allowing users to fit the desired model(s) and produce easy-to-interpret numerical and visual summaries.