Analyzing Incomplete Data Subject to a Threshold using Empirical Likelihood Methods: An Application to a Pneumonia Risk Study in an ICU Setting

被引:18
作者
Yu, Jihnhee [1 ]
Vexler, Albert [1 ]
Tian, Lili [1 ]
机构
[1] SUNY Buffalo, Dept Biostat, Buffalo, NY 14214 USA
关键词
Censored data; Empirical likelihood ratio test; Incomplete data; Linear regression; Nonparametric test; Two-sample test; Ventilator-associated pneumonia; VENTILATOR-ASSOCIATED PNEUMONIA; BRONCHOALVEOLAR LAVAGE; CONFIDENCE-INTERVALS; DIAGNOSIS;
D O I
10.1111/j.1541-0420.2009.01228.x
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
P>The initial detection of ventilator-associated pneumonia (VAP) for inpatients at an intensive care unit needs composite symptom evaluation using clinical criteria such as the clinical pulmonary infection score (CPIS). When CPIS is above a threshold value, bronchoalveolar lavage (BAL) is performed to confirm the diagnosis by counting actual bacterial pathogens. Thus, CPIS and BAL results are closely related and both are important indicators of pneumonia whereas BAL data are incomplete. To compare the pneumonia risks among treatment groups for such incomplete data, we derive a method that combines nonparametric empirical likelihood ratio techniques with classical testing for parametric models. This technique augments the study power by enabling us to use any observed data. The asymptotic property of the proposed method is investigated theoretically. Monte Carlo simulations confirm both the asymptotic results and good power properties of the proposed method. The method is applied to the actual data obtained in clinical practice settings and compares VAP risks among treatment groups.
引用
收藏
页码:123 / 130
页数:8
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