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The SURVEYREG Procedure |

**CONTRAST***'label' effect values < / options >***;**

**CONTRAST***'label' effect values < ... effect values > < / options >***;**

Each term in the MODEL statement, called an

For each CONTRAST statement, PROC SURVEYREG computes Wald's

You can specify any number of CONTRAST statements, but they must appear after the MODEL statement.

In the CONTRAST statement,

*label*- identifies the contrast in the output.
A label is required for every contrast
specified. Labels must be enclosed in
single quotes.

*effect*- identifies an
effect that appears in the MODEL
statement.
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.

*values*- are constants that are elements of
**L**associated with the effect.

You can specify the following options in the CONTRAST statement after a slash (/).

**E**-
displays the entire coefficient
**L**vector or matrix.

**NOFILL**-
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. **SINGULAR=***value*-
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 with commas. For example, for the modelproc surveyreg; class A B; model Y=A B; run;

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:contrast 'A Linear & Quadratic' a -2 -1 0 1 2, a 2 -1 -2 -1 2;

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