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Confidence intervals for difference between two binomial proportions derived from logistic regression

発表形態:
原著論文
主要業績:
主要業績
単著・共著:
共著
発表年月:
2022年
DOI:
10.1080/03610918.2019.1710195
会議属性:
指定なし
査読:
有り
リンク情報:

日本語フィールド

著者:
*Uozumi R, Yada S, Maruo K, Kawaguchi A
題名:
Confidence intervals for difference between two binomial proportions derived from logistic regression
発表情報:
Commun. Stat. Theory Methods 巻: 51 号: 6 ページ: 3223-3236
キーワード:
概要:
A common method of reporting the result of logistic regression is to provide an odds ratio and its corresponding confidence interval. The results of such statistical analyses cannot be further evaluated with respect to the consistency of confidence intervals between the odds ratio and the difference between proportions. In this paper, we propose a simple method to construct the confidence intervals for the difference between binomial proportions based on parameter estimates of logistic regression. Simulation results showed that the score-based confidence interval based on the sample marginal approach is a recommended method for sensitivity analysis in randomized clinical trials.
抄録:

英語フィールド

Author:
*Uozumi R, Yada S, Maruo K, Kawaguchi A
Title:
Confidence intervals for difference between two binomial proportions derived from logistic regression
Announcement information:
Commun. Stat. Theory Methods Vol: 51 Issue: 6 Page: 3223-3236
An abstract:
A common method of reporting the result of logistic regression is to provide an odds ratio and its corresponding confidence interval. The results of such statistical analyses cannot be further evaluated with respect to the consistency of confidence intervals between the odds ratio and the difference between proportions. In this paper, we propose a simple method to construct the confidence intervals for the difference between binomial proportions based on parameter estimates of logistic regression. Simulation results showed that the score-based confidence interval based on the sample marginal approach is a recommended method for sensitivity analysis in randomized clinical trials.


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