NESTED Procedure
The NESTED procedure performs randomeffects analysis of variance for data from an experiment with a nested (hierarchical) structure.
The following are highlights of the NESTED procedure's features:
 provides a descriptive analysis of covariation
 accommodates unbalanced data
 automatically displays the following for each dependent variable:
 Coefficients of Expected Mean Squares
 each Variance Source in the model (the different components of variance) and the total variance
 degrees of freedom (DF) for the corresponding sum of squares
 Sum of Squares for each classification factor
 F Value for a factor and the significance levels of a test of the hypothesis that each variance component equals zero
 the appropriate Error Term for an F test
 Mean Square due to a factor
 estimates of the Variance Components
 Percent of Total (the proportion of variance due to each source)
 Mean

 automatically displays the following when there are multiple dependent variables:
 degrees of freedom
 sum of products
 mean products
 covariance component
 variance component correlation
 mean square correlation
 performs BY group processing, which enables you to obtain separate analyses on grouped observations
 creates a SAS data set that corresponds to any output table

For further details see the SAS/STAT User's Guide:
The NESTED Procedure
( PDF  HTML )
Examples