通过经验似然比较分布函数

IF 1.2 4区数学 International Journal of Biostatistics Pub Date : 2006-01-04 DOI:10.2202/1557-4679.1007

I. McKeague, Yichuan Zhao

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引用次数: 40

摘要

本文开发了基于经验似然的两个分布函数的差异和比值的同时置信带，这些分布函数来自独立的右截尾生存数据样本。所提出的置信带提供了一种灵活的方法来比较生物医学环境中的治疗，并将经验似然方法应用于文献中只有wald型置信带可用的重要目标函数。通过一个实际数据示例说明了该方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Comparing Distribution Functions via Empirical Likelihood

This paper develops empirical likelihood based simultaneous confidence bands for differences and ratios of two distribution functions from independent samples of right-censored survival data. The proposed confidence bands provide a flexible way of comparing treatments in biomedical settings, and bring empirical likelihood methods to bear on important target functions for which only Wald-type confidence bands have been available in the literature. The approach is illustrated with a real data example.

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来源期刊

International Journal of Biostatistics Mathematics-Statistics and Probability

CiteScore

2.30

自引率

8.30%

发文量

期刊介绍： The International Journal of Biostatistics (IJB) seeks to publish new biostatistical models and methods, new statistical theory, as well as original applications of statistical methods, for important practical problems arising from the biological, medical, public health, and agricultural sciences with an emphasis on semiparametric methods. Given many alternatives to publish exist within biostatistics, IJB offers a place to publish for research in biostatistics focusing on modern methods, often based on machine-learning and other data-adaptive methodologies, as well as providing a unique reading experience that compels the author to be explicit about the statistical inference problem addressed by the paper. IJB is intended that the journal cover the entire range of biostatistics, from theoretical advances to relevant and sensible translations of a practical problem into a statistical framework. Electronic publication also allows for data and software code to be appended, and opens the door for reproducible research allowing readers to easily replicate analyses described in a paper. Both original research and review articles will be warmly received, as will articles applying sound statistical methods to practical problems.