中截尾寿命数据分析的半参数回归模型

IF 1.6 Q1 STATISTICS & PROBABILITY Statistica Pub Date : 2016-03-31 DOI:10.6092/ISSN.1973-2201/6281
S. Jammalamadaka, S. Prasad, P. G. Sankaran
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引用次数: 3

摘要

Jammalamadaka和Mangalam(2003)提出的中间审查是指,如果数据处于一个随机的审查区间内,那么它的确切寿命就变得不可观察,否则它是可观察的。在本文中,我们提出了这种寿命数据的半参数回归模型,这些数据来自未知的总体,并受到中间审查。我们提供了一种求回归参数和生存函数的非参数极大似然估计的算法。建立了估计量的相合性。我们报告模拟研究,以评估估计器的有限样本性质。然后,我们分析了Lee等人(1988)研究的糖尿病患者生存时间的真实生活数据。
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A SEMI-PARAMETRIC REGRESSION MODEL FOR ANALYSIS OF MIDDLE CENSORED LIFETIME DATA
Middle censoring introduced by Jammalamadaka and Mangalam (2003), refers to data arising in situations where the exact lifetime becomes unobservable if it falls within a random censoring interval, otherwise it is observable. In the present paper we propose a semi-parametric regression model for such lifetime data, arising from an unknown population and subject to middle censoring. We provide an algorithm to find the nonparametric maximum likelihood estimator (NPMLE) for regression parameters and the survival function. The consistency of the estimators are established. We report simulation studies to assess the finite sample properties of the estimators. We then analyze a real life data on survival times for diabetic patients studied by Lee et al. (1988).
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来源期刊
Statistica
Statistica STATISTICS & PROBABILITY-
CiteScore
1.70
自引率
0.00%
发文量
0
审稿时长
10 weeks
期刊最新文献
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