Absorption is a computational technique that provides a large reduction in time and memory requirements for certain types of models. The variables are one or more variables in the input data set.

For a main-effect variable that does not participate in interactions, you can absorb the effect by naming it in an ABSORB statement. This means that the effect can be adjusted out before the construction and solution of the rest of the model. This is particularly useful when the effect has a large number of levels.

Several variables can be specified, in which case each one is assumed to be nested in the preceding variable in the ABSORB statement.

Note:When you use the ABSORB statement, the data set (or each BY group, if a BY statement appears) must be sorted by the variables in the ABSORB statement. The GLM procedure cannot produce predicted values or least squares means (LS-means) or create an output data set of diagnostic values if an ABSORB statement is used. If the ABSORB statement is used, it must appear before the first RUN statement; otherwise, it is ignored.

When you use an ABSORB statement and also use the INT option in the MODEL statement, the procedure ignores the option but computes the uncorrected total sum of squares (SS) instead of the corrected total sums of squares.

See the section Absorption for more information.