Confidence interval estimation of a common correlation coefficient

Lili Tian; Gregory E. Wilding

doi:10.1016/j.csda.2008.04.002

Confidence interval estimation of a common correlation coefficient

Department of Biostatistics

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

Abstract

This paper presents a generalized variable approach for confidence interval estimation of a common correlation coefficient from several independent samples drawn from bivariate normal populations. This approach can provide one-sided bounds and two-sided confidence intervals with satisfying coverage probabilities regardless of the number of samples, sample sizes and magnitude of the common correlation coefficient while the large sample approach can be very liberal for one-sided bounds. The large sample approach generally performs well for two-sided confidence interval estimation.

Original language	English
Pages (from-to)	4872-4877
Number of pages	6
Journal	Computational Statistics and Data Analysis
Volume	52
Issue number	10
DOIs	https://doi.org/10.1016/j.csda.2008.04.002
State	Published - Jun 15 2008

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10.1016/j.csda.2008.04.002

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title = "Confidence interval estimation of a common correlation coefficient",

abstract = "This paper presents a generalized variable approach for confidence interval estimation of a common correlation coefficient from several independent samples drawn from bivariate normal populations. This approach can provide one-sided bounds and two-sided confidence intervals with satisfying coverage probabilities regardless of the number of samples, sample sizes and magnitude of the common correlation coefficient while the large sample approach can be very liberal for one-sided bounds. The large sample approach generally performs well for two-sided confidence interval estimation.",

author = "Lili Tian and Wilding, \{Gregory E.\}",

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T1 - Confidence interval estimation of a common correlation coefficient

AU - Tian, Lili

AU - Wilding, Gregory E.

PY - 2008/6/15

Y1 - 2008/6/15

N2 - This paper presents a generalized variable approach for confidence interval estimation of a common correlation coefficient from several independent samples drawn from bivariate normal populations. This approach can provide one-sided bounds and two-sided confidence intervals with satisfying coverage probabilities regardless of the number of samples, sample sizes and magnitude of the common correlation coefficient while the large sample approach can be very liberal for one-sided bounds. The large sample approach generally performs well for two-sided confidence interval estimation.

AB - This paper presents a generalized variable approach for confidence interval estimation of a common correlation coefficient from several independent samples drawn from bivariate normal populations. This approach can provide one-sided bounds and two-sided confidence intervals with satisfying coverage probabilities regardless of the number of samples, sample sizes and magnitude of the common correlation coefficient while the large sample approach can be very liberal for one-sided bounds. The large sample approach generally performs well for two-sided confidence interval estimation.

UR - https://www.scopus.com/pages/publications/44349086881

U2 - 10.1016/j.csda.2008.04.002

DO - 10.1016/j.csda.2008.04.002

M3 - Article

AN - SCOPUS:44349086881

SN - 0167-9473

VL - 52

SP - 4872

EP - 4877

JO - Computational Statistics and Data Analysis

JF - Computational Statistics and Data Analysis

IS - 10

ER -

Confidence interval estimation of a common correlation coefficient

Abstract

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