R and S-Plus Companion to Applied Regression
R and S-Plus Companion to Applied Regression
Improved estimation of clutter properties in speckled imagery
Computational Statistics & Data Analysis
Improved inference on a scalar fixed effect of interest in nonlinear mixed-effects models
Computational Statistics & Data Analysis
Improved testing inference in mixed linear models
Computational Statistics & Data Analysis
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The small-sample performance of alternatives to the usual likelihood ratio test in mixed linear models is investigated. Specifically, the following tests for fixed effects are considered: (i) a bootstrap-based test, (ii) the Bartlett-corrected usual test, and (iii) an adjusted profile likelihood ratio test. The last test is derived using an approximation to the modified profile likelihood proposed by Barndorff-Nielsen, based on the work of Severini. Bootstrap resampling is performed to numerically construct a Bartlett correction factor for the usual test statistic, and also to obtain a critical value that does not rely on first-order asymptotics. The numerical evidence presented in the paper slightly favors the Bartlett-corrected usual test. An application to real longitudinal data is presented.