## WEIGHT Statement

**WEIGHT** * variable ***;**

When a WEIGHT statement is used,
a weighted residual sum of squares

is minimized, where *w*_{i} is the value of the variable
specified in the WEIGHT statement, *y*_{i} is the observed
value of the response variable, and is the predicted value of the response variable.

If you specify the WEIGHT statement, it must appear
before the first RUN statement or it is ignored.

An observation is used in the analysis only if the value
of the WEIGHT statement variable is nonmissing and greater
than zero.

The WEIGHT statement has no effect on degrees of
freedom or number of observations, but it is used by the
MEANS statement when calculating means and performing
multiple comparison tests (as described in the "MEANS Statement" section).
The normal equations used when a WEIGHT statement is present are

where **W** is a diagonal matrix consisting of the
values of the variable specified in the WEIGHT statement.

If the weights for the observations are
proportional to the reciprocals of the error
variances, then the weighted least-squares
estimates are best linear unbiased estimators (BLUE).

Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.