期刊
BIOMETRICS
卷 68, 期 4, 页码 1074-1082出版社
WILEY-BLACKWELL
DOI: 10.1111/j.1541-0420.2012.01760.x
关键词
Cluster effects; Efficiency; Exchangeable error structure; Random effect; Rank regression; Working covariance matrix
资金
- Centre for Applications in Natural Resource Mathematics (CRAM), School of Mathematics and Physics, The University of Queensland, Australia
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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