Lack-of-Fit Tests in Semiparametric Mixed Models

23 Pages Posted: 3 Mar 2008

See all articles by Gerda Claeskens

Gerda Claeskens

KU Leuven - Department of Economics

Huijuan Ding

Katholieke Universiteit Leuven. KUL. Faculty of Business and Economics

Maarten Jansen

affiliation not provided to SSRN

Date Written: january 2007

Abstract

In this paper we obtain the asymptotic distribution of restricted likelihood ratio tests in mixed linear models with a fixed and finite number of random effects. We explain why for such models the often quoted 50:50 mixture of a chi-s quared random variable with one degree of freedom and a point mass at zero does not hold. Our motivation is a study of the use of wavelets for lack-of-fit testing within a mixed model framework. Even though wavelet shave received a lot of attention in the last say 15 years for the estimation of piecewise smooth functions, much less is known about their ability to check the adequacy of a parametric model when fitting the observed data. In particular we study the testing power of wavelets for testing a hypothesized parametric model within a mixed model framework. Experimental results show that in several situations the wavelet-based test significantly outperforms the com-petitor based on penalized regression splines. The obtained results are also applicable for testing in mixed models in general, and shed some new insight into previous results.

Keywords: Lack-off-fittest; Likelihood ratio test; Mixed models; One-sided test; Penalization; Restricted maximum likelihood; Variance components; Wavel; Asymptotic distribution; Distribution; Likelihood; Tests; Models; Model; Random effects; Effects; Studies; Lack-of-fit; Mixed model; Framework; Functions; D

Suggested Citation

Claeskens, Gerda and Ding, Huijuan and Jansen, Maarten, Lack-of-Fit Tests in Semiparametric Mixed Models (january 2007). Available at SSRN: https://ssrn.com/abstract=1099343 or http://dx.doi.org/10.2139/ssrn.1099343

Gerda Claeskens (Contact Author)

KU Leuven - Department of Economics ( email )

Leuven, B-3000
Belgium

Huijuan Ding

Katholieke Universiteit Leuven. KUL. Faculty of Business and Economics ( email )

Naamsestraat 69
Leuven, B-3000
Belgium

Maarten Jansen

affiliation not provided to SSRN ( email )

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