Non-parametric confidence interval estimation for competing risks analysis: application to contraceptive data
Non-parametric confidence interval estimation for competing risks analysis: application to contraceptive data
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DOI：
10.1002/sim.1070
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发表时间：
2002-04-30
影响因子：
2
通讯作者：
Choudhury, JB
中科院分区：
文献类型：
--
作者：
Choudhury, JB
参考孟加拉国的避孕药具使用动态数据，讨论了在存在竞争风险的情况下，特定原因失败概率及其标准误差的非参数最大似然估计。原因特定发生率函数基于特定事件的右审查数据，提供了关于失败率和概率的直观的吸引人的汇总曲线，例如不同类型避孕措施停止的概率。Dinse和Larson公式可用于计算感兴趣的故障类型的原因特定概率的标准误差，并构造逐点可信区间。通过仿真比较了这些区间以及基于对数(-LOG)变换和反正弦变换的区间的精度。我们发现，Dinse和Larson公式与对数(-log)变换结合使用，在小样本和大样本中都能得到可靠的标准误差估计和准确的覆盖，可推荐用于这种情况。版权所有(C)2002 John Wiley Sons，Ltd.
Non-parametric maximum likelihood estimation of the cause specific failure probability, and of its standard error, in the presence of competing risks is discussed with reference to some contraceptive use dynamics data from Bangladesh. The cause specific incidence function provides an intuitively appealing summary curve for failure rates and probabilities, such as probabilities of discontinuation of different kinds of contraception, based on right-censored data of the particular event. Dinse and Larson's formula can be utilized to calculate the standard error of the cause specific probability for the failure type of interest, and to construct pointwise confidence intervals. The accuracy of these intervals, as well as those based on the log(-log) transformation and the arcsine transformation, are compared by simulations. We find that Dinse and Larson's formula, used in conjuction with a log(-log) transform, yields reliable standard error estimates and accurate coverage in samples of small and large size, and can be recommended for use in this situation. Copyright (C) 2002 John Wiley Sons, Ltd.