Description Usage Arguments Details Value Author(s) References See Also Examples
This function provides an exact likelihood ratio test based on simulated values from the finite sample distribution for simultaneous testing of the presence of the variance component and some restrictions of the fixed effects in a simple linear mixed model with known correlation structure of the random effect and i.i.d. errors.
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m 
The fitted model under the alternative; of class 
m0 
The fitted model under the null hypothesis; of class 
seed 
Specify a seed for 
nsim 
Number of values to simulate 
log.grid.hi 
Lower value of the grid on the log scale. See

log.grid.lo 
Lower value of the grid on the log scale. See

gridlength 
Length of the grid. See 
parallel 
The type of parallel operation to be used (if any). If missing, the default is "no parallelization"). 
ncpus 
integer: number of processes to be used in parallel operation: typically one would chose this to the number of available CPUs. Defaults to 1, i.e., no parallelization. 
cl 
An optional parallel or snow cluster for use if parallel = "snow". If not supplied, a cluster on the local machine is created for the duration of the call. 
The model under the alternative must be a linear mixed model y=X*beta+Z*b+epsilon with a single random effect b with known correlation structure and error terms that are i.i.d. The hypothesis to be tested must be of the form
H0: beta_1=beta0_1,..,beta_q=beta0_q, Var(b)=0
H0: beta_1=beta0_1,..,beta_q=beta0_q, Var(b)=0
versus
H0: beta_1 \neq beta0_1,..or..,beta_q \neq beta0_q ot Var(b)>0
H0: beta_1 \neq beta0_1,..or..,beta_q \neq beta0_q ot Var(b)>0
We use the exact finite sample distribution of the likelihood ratio test statistic as derived by Crainiceanu & Ruppert (2004).
A list of class htest
containing the following components:
statistic
the observed likelihood ratio
p
pvalue for the observed test statistic
method
a character string indicating what type of test was
performed and how many values were simulated to determine the critical value
sample
the samples from the null distribution returned by
LRTSim
Fabian Scheipl, updates for lme4.0compatibility by Ben Bolker
Crainiceanu, C. and Ruppert, D. (2004) Likelihood ratio tests in linear mixed models with one variance component, Journal of the Royal Statistical Society: Series B,66,165–185.
LRTSim
for the underlying simulation algorithm;
RLRTSim
and exactRLRT
for restricted likelihood
based tests
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