Journal
BIOMETRICS
Volume 68, Issue 4, Pages 1074-1082Publisher
WILEY-BLACKWELL
DOI: 10.1111/j.1541-0420.2012.01760.x
Keywords
Cluster effects; Efficiency; Exchangeable error structure; Random effect; Rank regression; Working covariance matrix
Funding
- Centre for Applications in Natural Resource Mathematics (CRAM), School of Mathematics and Physics, The University of Queensland, Australia
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Rank-based inference is widely used because of its robustness. This article provides optimal rank-based estimating functions in analysis of clustered data with random cluster effects. The extensive simulation studies carried out to evaluate the performance of the proposed method demonstrate that it is robust to outliers and is highly efficient given the existence of strong cluster correlations. The performance of the proposed method is satisfactory even when the correlation structure is misspecified, or when heteroscedasticity in variance is present. Finally, a real dataset is analyzed for illustration.
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