New confidence intervals for the proportion of interest in one-sample correlated binary data

Seung Ho Kang, Yonghee Lee

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Correlated binary data is obtained in many fields of biomedical research. When constructing a confidence interval for the proportion of interest, asymptotic confidence intervals have already been developed. However, such asymptotic confidence intervals are unreliable in small samples. To improve the performance of asymptotic confidence intervals in small samples, we obtain the Edgeworth expansion of the distribution of the studentized mean of beta-binomial random variables. Then, we propose new asymptotic confidence intervals by correcting the skewness in the Edgeworth expansion in one direct and two indirect ways. New confidence intervals are compared with the existing confidence intervals in simulation studies.

Original languageEnglish
Pages (from-to)2865-2876
Number of pages12
JournalCommunications in Statistics - Theory and Methods
Volume39
Issue number16
DOIs
Publication statusPublished - 2010

Bibliographical note

Funding Information:
This work was supported by grant No. R01-2006-000-101650-2006 from the Basic Research Program of the Korea Science & Engineering Foundation.

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

Fingerprint

Dive into the research topics of 'New confidence intervals for the proportion of interest in one-sample correlated binary data'. Together they form a unique fingerprint.

Cite this