Goodness-of-fit test for semiparametric copula models with bivariate interval-censored data
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作者:
Zhang, Ximeng
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机构:
Jilin Univ, Ctr Appl Stat Res, Changchun, Peoples R China
Jilin Univ, Coll Math, Changchun, Peoples R ChinaJilin Univ, Ctr Appl Stat Res, Changchun, Peoples R China
Zhang, Ximeng
[1
,2
]
Zhao, Shishun
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机构:
Jilin Univ, Ctr Appl Stat Res, Changchun, Peoples R China
Jilin Univ, Coll Math, Changchun, Peoples R ChinaJilin Univ, Ctr Appl Stat Res, Changchun, Peoples R China
Zhao, Shishun
[1
,2
]
Hu, Tao
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机构:
Capital Normal Univ, Sch Math Sci, Beijing, Peoples R ChinaJilin Univ, Ctr Appl Stat Res, Changchun, Peoples R China
Hu, Tao
[3
]
Sun, Jianguo
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机构:
Univ Missouri, Dept Stat, Columbia, MO USAJilin Univ, Ctr Appl Stat Res, Changchun, Peoples R China
Sun, Jianguo
[4
]
机构:
[1] Jilin Univ, Ctr Appl Stat Res, Changchun, Peoples R China
[2] Jilin Univ, Coll Math, Changchun, Peoples R China
[3] Capital Normal Univ, Sch Math Sci, Beijing, Peoples R China
This paper discusses the goodness-of-fit test of semiparametric copula models when one faces bivariate interval-censored failure time data, which often occur in many areas including epidemiological and medical studies as well as social science experiments. For the problem, three test statistics or procedures are proposed: two based on the pseudo in-and-out-sample approach and one based on the information ratio criterion. The asymptotic properties of the proposed test procedures are established, and in particular, the three methods are shown to be asymptotically equivalent. To assess the empirical performance of the proposed methods, an extensive simulation study is conducted and indicates that they work well in practical situations. An application to a Signal-Tandmobiel study is provided.
机构:
Baylor Coll Med, Dan L Duncan Canc Ctr, Div Biostat, Houston, TX 77030 USABaylor Coll Med, Dan L Duncan Canc Ctr, Div Biostat, Houston, TX 77030 USA
Liu, Hao
Shen, Yu
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机构:
Univ Texas MD Anderson Canc Ctr, Dept Biostat, Houston, TX 77030 USABaylor Coll Med, Dan L Duncan Canc Ctr, Div Biostat, Houston, TX 77030 USA