- CONTRAST 'label' effect values < / options >
The CONTRAST statement provides custom hypothesis tests
for linear combinations of the regression parameters
, where L is the
vector or matrix you specify and is the vector
of regression parameters. Thus, to use this feature,
you must be familiar with the details of the model
parameterization used by PROC SURVEYREG.
For information on the parameterization, see
the section "Parameterization of PROC GLM Models" in Chapter 30, "The GLM Procedure.".
- CONTRAST 'label' effect values
< ... effect values >
< / options > ;
Each term in the MODEL statement, called an effect,
is a variable or a combination of variables. You can
specify an effect with a variable name or a special
notation using variable names and operators.
For more details on how to specify an effect, see
the section "Specification of Effects" in Chapter 30, "The GLM Procedure.".
For each CONTRAST statement, PROC SURVEYREG computes
Wald's F test. The procedure displays this value
with the degrees of freedom, and identifies it with the
contrast label. The numerator degrees of freedom for
Wald's F test equals rank(L). The
denominator degrees of freedom equals the number of
clusters (or the number of observations if there is no
CLUSTER statement) minus the number of strata.
Alternatively, you can use the DF= option in the MODEL
statement to specify the denominator degrees of freedom.
You can specify any number of CONTRAST statements,
but they must appear after the MODEL statement.
In the CONTRAST statement,
- identifies the contrast in the output.
A label is required for every contrast
specified. Labels must be enclosed in
- identifies an
effect that appears in the MODEL
You can use the INTERCEPT keyword 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.
- are constants that are elements of
L associated with the
You can specify the following options in the CONTRAST
statement after a slash (/).
displays the entire coefficient L vector or matrix.
requests no filling in higher-order effects. When you
specify only certain portions of L, by default
PROC SURVEYREG constructs the remaining elements from
the context (for more information, the section "Specification of ESTIMATE Expressions" in
Chapter 30, "The GLM Procedure.").
When you specify the NOFILL option, PROC SURVEYREG does not construct the
remaining portions and treats the vector or matrix
L as it is defined in the CONTRAST statement.
specifies the sensitivity for checking estimability.
If v is a vector, define ABS(v) to be the largest absolute value of the elements
of v. Say H
is the (X'X)-X'X matrix,
and C is ABS(L)
except for elements of L that equal 0, and then
C is 1.
If ABS(L-LH) > C ·
value, then L is declared nonestimable. The
SINGULAR=value must be between 0 and 1, and the
default is 10-4.
As stated previously, the CONTRAST statement enables you
to perform hypothesis tests .
If the L matrix contains more than one contrast,
then you can separate the rows of the L matrix
For example, for the model
class A B;
model Y=A B;
with A at 5 levels and B at 2 levels, the
parameter vector is
To test the hypothesis that the pooled A linear and
A quadratic effect is zero, you can use the
following L matrix:
The corresponding CONTRAST statement is
contrast 'A Linear & Quadratic'
a -2 -1 0 1 2,
a 2 -1 -2 -1 2;
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.