Abstract
The confidence level of the usual interval for a ratio of variance components is contingent on normally distributed random variables. In this article we focus on confidence intervals for ratios of variance components in balanced one-way random effects models based on the large-sample properties of restricted maximum likelihood (REML) estimators. While this procedure does not require that the random variables be normally distributed, one must estimate a parameter that is a function of the kurtosis of the underlying distributions. Simulation results indicate that REML-based confidence interval methods outperform other well-known methods in the majority of the cases considered.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 349-362 |
| Number of pages | 14 |
| Journal | Communications in Statistics - Theory and Methods |
| Volume | 44 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jan 17 2015 |
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Keywords
- Intraclass correlation coefficient
- One-way random effects model
- REML
ASJC Scopus subject areas
- Statistics and Probability
Cite this
Improved large-sample confidence intervals for ratios of variance components in nonnormal distributions. / Burch, Brent D.
In: Communications in Statistics - Theory and Methods, Vol. 44, No. 2, 17.01.2015, p. 349-362.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Improved large-sample confidence intervals for ratios of variance components in nonnormal distributions
AU - Burch, Brent D
PY - 2015/1/17
Y1 - 2015/1/17
N2 - The confidence level of the usual interval for a ratio of variance components is contingent on normally distributed random variables. In this article we focus on confidence intervals for ratios of variance components in balanced one-way random effects models based on the large-sample properties of restricted maximum likelihood (REML) estimators. While this procedure does not require that the random variables be normally distributed, one must estimate a parameter that is a function of the kurtosis of the underlying distributions. Simulation results indicate that REML-based confidence interval methods outperform other well-known methods in the majority of the cases considered.
AB - The confidence level of the usual interval for a ratio of variance components is contingent on normally distributed random variables. In this article we focus on confidence intervals for ratios of variance components in balanced one-way random effects models based on the large-sample properties of restricted maximum likelihood (REML) estimators. While this procedure does not require that the random variables be normally distributed, one must estimate a parameter that is a function of the kurtosis of the underlying distributions. Simulation results indicate that REML-based confidence interval methods outperform other well-known methods in the majority of the cases considered.
KW - Intraclass correlation coefficient
KW - One-way random effects model
KW - REML
UR - http://www.scopus.com/inward/record.url?scp=84919629092&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84919629092&partnerID=8YFLogxK
U2 - 10.1080/03610926.2012.743567
DO - 10.1080/03610926.2012.743567
M3 - Article
AN - SCOPUS:84919629092
VL - 44
SP - 349
EP - 362
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
SN - 0361-0926
IS - 2
ER -