Restricted Likelihood Ratio Testing for Zero Variance Components in Linear Mixed Models

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Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models (2008, background): “Greven et al. (2007) suggest simulating the distribution of RLRT based on the reduced model under the assumption of known nuisance random effect parameters.”
A general framework for functional regression modelling (2017, background): “This also holds—at least to some extent—for inference in such models (e.g., Greven et al., 2008; Scheipl et al., 2008; Wood, 2013) and its transfer to functional regression (e.g., Staicu et al., 2014; Swihart et al., 2014; McLean et al., 2015).”
A simple test for random effects in regression models (2013, methodology): “The latter is an approximation proposed by Greven et al. (2008) based on the exact test of Crainiceanu & Ruppert (2004) and Crainiceanu et al. (2005) and implemented in R (R Development Core Team, 2013) package RLRsim.”
How Much of Interviewer Variance is Really Nonresponse Error Variance (2010, background): “A likelihood ratio test(6) for the variance component has been shown to have better statistical properties (Self and Liang 1987; Stram and Lee 1994), yet recent simulation studies have demonstrated that the likelihood ratio test statistic has a more complicated distribution in many practical situati”