Robustified Maximum Likelihood Estimation in Generalized Partial Linear Mixed Model for Longitudinal Data
Version of Record online: 13 MAY 2008
© 2008, The International Biometric Society
Volume 65, Issue 1, pages 52–59, March 2009
How to Cite
You Qin, G. and Yi Zhu, Z. (2009), Robustified Maximum Likelihood Estimation in Generalized Partial Linear Mixed Model for Longitudinal Data. Biometrics, 65: 52–59. doi: 10.1111/j.1541-0420.2008.01050.x
- Issue online: 17 MAR 2009
- Version of Record online: 13 MAY 2008
- Received July 2007. Revised February 2008. Accepted February 2008.
- Mixed model;
- Partial linear model;
- Penalized spline;
- Variance components
Summary In this article, we study the robust estimation of both mean and variance components in generalized partial linear mixed models based on the construction of robustified likelihood function. Under some regularity conditions, the asymptotic properties of the proposed robust estimators are shown. Some simulations are carried out to investigate the performance of the proposed robust estimators. Just as expected, the proposed robust estimators perform better than those resulting from robust estimating equations involving conditional expectation like Sinha (2004, Journal of the American Statistical Association99, 451–460) and Qin and Zhu (2007, Journal of Multivariate Analysis98, 1658–1683). In the end, the proposed robust method is illustrated by the analysis of a real data set.