ESTIMATE Statement
 ESTIMATE 'label' effect values < ...
effect values > < /
options > ;
The ESTIMATE statement enables you to estimate linear functions
of the parameters by multiplying the vector L by the
parameter estimate vector b resulting in Lb.
All of the elements of the L vector may be
given, or, if only certain portions of the L
vector are given, the remaining elements are constructed
by PROC GLM from the context (in a manner similar to rule 4
discussed in the "Construction of LeastSquares Means" section).
The linear function is checked for estimability.
The estimate Lb, where
b = (X'X)^{}X'y,
is displayed along with its associated standard error,
,and t test.
If you specify the CLPARM option in the MODEL
statement, confidence limits
for the true value are also displayed.
There is no limit to the number of ESTIMATE statements that you can specify,
but they must appear after the MODEL statement.
In the ESTIMATE statement,
 label
 identifies the estimate on the output.
A label is required for every contrast specified.
Labels must be enclosed in quotes.
 effect
 identifies an effect that appears in the MODEL statement, or
the INTERCEPT effect.
The INTERCEPT effect can be used as an effect when
an intercept is fitted in the model.
You do not need to include all effects
that are in the MODEL statement.
 values
 are constants that are the elements of the L
vector associated with the preceding effect.
For example,
estimate 'A1 VS A2' A 1 1;
forms an estimate that is the difference between the parameters
estimated for the first and second levels of the CLASS variable A.
You can specify the following options in the
ESTIMATE statement after a slash:
 DIVISOR=number

specifies a value by which to divide all coefficients so that
fractional coefficients can be entered as integer numerators.
For example, you can use
estimate '1/3(A1+A2)  2/3A3' a 1 1 2 / divisor=3;
instead of
estimate '1/3(A1+A2)  2/3A3' a 0.33333 0.33333 0.66667;
 E

displays the entire L
vector. This option is useful in
confirming the ordering of parameters for specifying
L.
 SINGULAR=number

tunes the estimability checking.
If ABS(L  LH) > C×number,
then the L vector is declared nonestimable.
H is the (X'X)^{}X'X
matrix, and C is ABS(L) except for rows where
L is zero, and then it is 1.
The default value for the SINGULAR= option is 10^{4}.
Values for the SINGULAR= option must be between 0 and 1.
See also the "Specification of ESTIMATE Expressions" section.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.