Assessing and comparing the accuracy of various bootstrap methods

被引：2

作者：

Zhu, Yaqian ^{[1
]}

Kolassa, John ^{[1
]}

机构：

[1] Rutgers State Univ, Dept Stat & Biostat, New Brunswick, NJ USA

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2018年 / 47卷 / 08期

基金：

美国国家科学基金会;

关键词：

Accelerated failure time model; Bootstrap; Cox regression model; CONFIDENCE-INTERVALS;

D O I：

10.1080/03610918.2017.1348516

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We evaluate the performance of various bootstrap methods for constructing confidence intervals for mean and median of several common distributions. Using Monte Carlo simulation, we assessed performance by looking at coverage percentages and average confidence interval lengths. Poor performance is characterized by coverage deviating from 0.95 and large confidence interval lengths. Undercoverage is of greater concern than overcoverage. We also assess the performance of bootstrap methods in estimating the parameters of the Cox Proportional Hazard model and Accelerated Failure Time model.

引用

页码：2436 / 2453

页数：18

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