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The GENMOD Procedure |

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

The CONTRAST statement provides a means for obtaining a test for a specified hypothesis concerning the model parameters. This is accomplished by specifying a matrix

There is no limit to the number of CONTRAST statements that you can specify, but they must appear after the MODEL statement. Statistics for multiple CONTRAST statements are displayed in a single table.

The following parameters are specified in the CONTRAST statement:

*label*- identifies the contrast on the output.
A label is required for every contrast specified.
Labels can be up to 20 characters
and must be enclosed in single quotes.
*effect*- identifies an effect that appears in the MODEL statement.
The value INTERCEPT or intercept can be used as an effect when
an intercept is included in the model.
You do not need to include all effects
that are included in the MODEL statement.
*values*- are constants that are elements of the
**L**vector associated with the effect.

The rows of

If an effect is not specified in the CONTRAST statement, all of its coefficients in the

PROC GENMOD handles missing level combinations of classification variables in the same manner as the GLM and MIXED procedures. Parameters corresponding to missing level combinations are not included in the model. This convention can affect the way in which you specify the

If the elements of

If you specify the WALD option, the test of hypothesis is based on a Wald chi-square statistic. If you omit the WALD option, the test statistic computed depends on whether an ordinary generalized linear model or a GEE-type model is specified.

For an ordinary generalized linear model, the CONTRAST statement computes the likelihood ratio statistic. This is defined to be twice the difference between the log likelihood of the model unconstrained by the contrast and the log likelihood with the model fitted under the constraint that the linear function of the parameters defined by the contrast is equal to 0. A

If you specify a GEE model with the REPEATED statement, the test is based on a score statistic. The GEE model is fit under the constraint that the linear function of the parameters defined by the contrast is equal to 0. The score chi-square statistic is computed based on the generalized score function. See the "Generalized Score Statistics" section for more information.

The degrees of freedom is the number of linearly independent constraints implied by the CONTRAST statement, that is, the rank of

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

**E**-
requests that the
**L**matrix be displayed. **SINGULAR =***number*-
tunes the estimability checking.
If
**v**is a vector, define ABS(**v**) to be the absolute value of the element of**v**with the largest absolute value. Define C to be equal to ABS(**K'**) if ABS(**K'**) is greater than 0; otherwise, C equals 1 for a row**K'**in the contrast. If ABS(**K' - K'T**) is greater than C**number*, then**K**is declared nonestimable.**T**is the Hermite form matrix**(X'X)**, and^{-}(X'X)**(X'X)**represents a generalized inverse of the matrix^{-}**X'X**. The value for*number*must be between 0 and 1; the default value is 1E-4. **WALD**-
requests that a Wald chi-square statistic be computed for the
contrast rather than the default likelihood ratio or score statistic.
The Wald statistic for testing
is defined by
*S*is , where*r*is the rank of**L**. Computed*p*-values are based on this distribution.

If you specify a GEE model with the REPEATED statement, is the empirical covariance matrix estimate.

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