### Abstract

The conventional confidence interval for the intraclass correlation coefficient assumes equal-tail probabilities. In general, the equal-tail probability interval is biased and other interval procedures should be considered. Unbiased confidence intervals for the intraclass correlation coefficient are readily available. The equal-tail probability and unbiased intervals have exact coverage as they are constructed using the pivotal quantity method. In this article, confidence intervals for the intraclass correlation coefficient are built using balanced and unbalanced one-way random effects models. The expected length of confidence intervals serves as a tool to compare the two procedures. The unbiased confidence interval outperforms the equal-tail probability interval if the intraclass correlation coefficient is small and the equal-tail probability interval outperforms the unbiased interval if the intraclass correlation coefficient is large.

Original language | English (US) |
---|---|

Pages (from-to) | 3264-3275 |

Number of pages | 12 |

Journal | Communications in Statistics - Theory and Methods |

Volume | 37 |

Issue number | 20 |

DOIs | |

State | Published - Dec 2008 |

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### Keywords

- Expected length
- Ghosh-Pratt identity
- One-way random effects model
- Variance components

### ASJC Scopus subject areas

- Statistics and Probability
- Safety, Risk, Reliability and Quality

### Cite this

**Comparing equal-tail probability and unbiased confidence intervals for the intraclass correlation coefficient.** / Burch, Brent D.

Research output: Contribution to journal › Article

}

TY - JOUR

T1 - Comparing equal-tail probability and unbiased confidence intervals for the intraclass correlation coefficient

AU - Burch, Brent D

PY - 2008/12

Y1 - 2008/12

N2 - The conventional confidence interval for the intraclass correlation coefficient assumes equal-tail probabilities. In general, the equal-tail probability interval is biased and other interval procedures should be considered. Unbiased confidence intervals for the intraclass correlation coefficient are readily available. The equal-tail probability and unbiased intervals have exact coverage as they are constructed using the pivotal quantity method. In this article, confidence intervals for the intraclass correlation coefficient are built using balanced and unbalanced one-way random effects models. The expected length of confidence intervals serves as a tool to compare the two procedures. The unbiased confidence interval outperforms the equal-tail probability interval if the intraclass correlation coefficient is small and the equal-tail probability interval outperforms the unbiased interval if the intraclass correlation coefficient is large.

AB - The conventional confidence interval for the intraclass correlation coefficient assumes equal-tail probabilities. In general, the equal-tail probability interval is biased and other interval procedures should be considered. Unbiased confidence intervals for the intraclass correlation coefficient are readily available. The equal-tail probability and unbiased intervals have exact coverage as they are constructed using the pivotal quantity method. In this article, confidence intervals for the intraclass correlation coefficient are built using balanced and unbalanced one-way random effects models. The expected length of confidence intervals serves as a tool to compare the two procedures. The unbiased confidence interval outperforms the equal-tail probability interval if the intraclass correlation coefficient is small and the equal-tail probability interval outperforms the unbiased interval if the intraclass correlation coefficient is large.

KW - Expected length

KW - Ghosh-Pratt identity

KW - One-way random effects model

KW - Variance components

UR - http://www.scopus.com/inward/record.url?scp=51149115323&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=51149115323&partnerID=8YFLogxK

U2 - 10.1080/03610920802162631

DO - 10.1080/03610920802162631

M3 - Article

VL - 37

SP - 3264

EP - 3275

JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

SN - 0361-0926

IS - 20

ER -