Small sample inference for fixed effects from restricted maximum likelihood.

@article{Kenward1997SmallSI,
  title={Small sample inference for fixed effects from restricted maximum likelihood.},
  author={Michael G. Kenward and James H. Roger},
  journal={Biometrics},
  year={1997},
  volume={53 3},
  pages={
          983-97
        }
}
Restricted maximum likelihood (REML) is now well established as a method for estimating the parameters of the general Gaussian linear model with a structured covariance matrix, in particular for mixed linear models. Conventionally, estimates of precision and inference for fixed effects are based on their asymptotic distribution, which is known to be inadequate for some small-sample problems. In this paper, we present a scaled Wald statistic, together with an F approximation to its sampling… 
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    Commun. Stat. Simul. Comput.
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