Efficient Estimation for Rank-Based Regression with Clustered Data
Version of Record online: 29 MAR 2012
© 2012, The International Biometric Society
Volume 68, Issue 4, pages 1074–1082, December 2012
How to Cite
Fu, L. and Wang, Y.-G. (2012), Efficient Estimation for Rank-Based Regression with Clustered Data. Biometrics, 68: 1074–1082. doi: 10.1111/j.1541-0420.2012.01760.x
- Issue online: 21 DEC 2012
- Version of Record online: 29 MAR 2012
- Received June 2011. Revised December 2011. Accepted February 2012.
- Cluster effects;
- Exchangeable error structure;
- Random effect;
- Rank regression;
- Working covariance matrix
Summary 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.