City Research Online

Abstract

© 2016 Biometrika Trust.We address the problem of testing for a parametric function of fixed effects in mixed models. We propose a test based on the distance between two empirical error distribution functions, which are constructed from residuals calculated under the opposing hypotheses. The proposed test statistic has power against all alternatives, and its asymptotic distribution is derived. A simulation study shows that the test outperforms others in the literature. The test is applied to longitudinal data from an AIDS clinical trial and a growth study.

Publication Type:	Article
Additional Information:	This is the peer reviewed version of the following article: González-Manteiga, W., Martinez-Miranda, M. D. & Van Keilegom, I. (2016). Goodness-of-fit test in parametric mixed effects models based on estimation of the error distribution. Biometrika, 103(1), pp. 133-146, which has been published in final form at https://dx.doi.org/10.1093/biomet/asv061. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Publisher Keywords:	Bootstrap, Empirical distribution, Local polynomial estimation, Mixed model, Residual
Subjects:	H Social Sciences > HA Statistics
Departments:	Bayes Business School > Actuarial Science & Insurance
SWORD Depositor:	Symplectic Administrator

Export

Downloads