User Guide

37
Variance Components Analysis
Variance Components Options
Figure 3-3
Variance Components Options dialog box
Method. You can choose one of four methods used to estimate the variance
components.
 MINQUE (minimum norm quadratic unbiased estimator) produces estimates that
are invariant with respect to the fixed effects. If the data are normally distributed
and the estimates are correct, this method produces the least variance among all
unbiased estimators. You can choose a method for random-effect prior weights.
 ANOVA (analysis of variance) computes unbiased estimates using either the Type I
or Type III sums of squares for each effect. The ANOVA method sometimes
produces negative variance estimates, which can indicate an incorrect model, an
inappropriate estimation method, or a need for more data.
 Maximum likelihood (ML) produces estimates that would be most consistent with the
data actually observed, using iterations. These estimates can be biased. This
method is asymptotically normal. ML and REML estimates are invariant under
translation. This method does not take into account the degrees of freedom used to
estimate the fixed effects.
 Restricted maximum likelihood (REML) estimates reduce the ANOVA estimates for
many (if not all) cases of balanced data. Because this method is adjusted for the
fixed effects, it should have smaller standard errors than the ML method. This
method takes into account the degrees of freedom used to estimate the fixed effects.