Wilson Confidence Intervals for Binomial Proportions With Multiple Imputation for Missing Data

被引：19

作者：

Lott, Anne ^{[1
]}

Reiter, Jerome P. ^{[1
]}

机构：

[1] Duke Univ, Dept Stat Sci, Durham, NC 27708 USA

来源：

AMERICAN STATISTICIAN | 2020年 / 74卷 / 02期

基金：

美国国家科学基金会;

关键词：

Binomial; Incomplete; Missing; Proportion; INFERENCE; MODELS;

D O I：

10.1080/00031305.2018.1473796

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 present a Wilson interval for binomial proportions for use with multiple imputation for missing data. Using simulation studies, we show that it can have better repeated sampling properties than the usual confidence interval for binomial proportions based on Rubin's combining rules. Further, in contrast to the usual multiple imputation confidence interval for proportions, the multiple imputation Wilson interval is always bounded by zero and one. Supplementary material is available online.

引用

页码：109 / 115

页数：7

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