Bartlett-type adjustments for hypothesis testing in linear models with general error covariance matrices

Masahiro Kojima and Tatsuya Kubokawa

Journal of Multivariate Analysis, 2013, vol. 122, issue C, 162-174

Abstract: Consider the problem of testing a linear hypothesis of regression coefficients in a general linear regression model with a covariance matrix involving several nuisance parameters. Then, the Bartlett-type adjustments of the Wald, Score, and modified Likelihood Ratio tests are derived for general consistent estimators of the unknown nuisance parameters. The adjusted test statistics have second-order corrections in type I errors. Simple parametric bootstrap methods are also suggested for estimating the Bartlett-type adjustments and it is shown that they have the second order accuracy.

Keywords: Bartlett-type adjustment; Linear mixed model; Parametric bootstrap (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1016/j.jmva.2013.07.016

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