A nonparametric vertical model : an application to discrete time competing risks data with missing failure causes
A nonparametric vertical model : an application to discrete time competing risks data with missing failure causes
复制标题
非参数垂直模型：在缺少故障原因的离散时间竞争风险数据中的应用
DOI：
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发表时间：
2020
影响因子：
0.3
通讯作者：
T. Zewotir
中科院分区：
文献类型：
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作者：
B. Ndlovu;S. Melesse;T. Zewotir
在社会科学，教育等领域，其中故障时间通常以离散单位测量。对于某些受试者，该数据也可能存在未知的失败原因。这发生在非常有限的离散时间分析方法的背景下，这些方法被开发用于处理这些数据。多年来，已经提出了许多连续时间缺失失效原因模型。我们选择这些连续时间模型之一，垂直模型（Nicolaie等人，2015），并将其作为非参数模型，可应用于缺失失效原因的离散时间竞争风险数据。该模型被应用到真实的数据和MI相比。结果发现，所提出的模型相比，毫不逊色MI方法。
Discretetimecompetingrisksdatacontinuetoariseinsocialsciences,educationetc.,where time to failure is usually measured in discrete units. This data may also come with unknown failure causes for some subjects. This occurs against a background of very limited discrete time analysis methods that were developed to handle such data. A number of continuous time missing failure causes models have been proposed over the years. We select one of these continuous time models, the vertical model (Nicolaie et al., 2015), and present it as a nonparametric model that can be applied to discrete time competing risks data with missing failure causes. The proposed model is applied to real data and compared to the MI. It was found that the proposed model compared favorably with the MI method.
DOI：
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发表时间：
2013-12
期刊：
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影响因子：
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作者：
M. Betancur
通讯作者：
M. Betancur
影响因子：
1.9
作者：
DINSE, GE
通讯作者：
DINSE, GE