The PLM Procedure |
ESTIMATE Statement |
The ESTIMATE statement provides a mechanism for obtaining custom hypothesis tests. Estimates are formed as linear estimable functions of the form . You can perform hypothesis tests for the estimable functions, construct confidence limits, and obtain specific nonlinear transformations.
Table 66.3 summarizes important options in the ESTIMATE statement.
Option |
Description |
---|---|
Construction and Computation of Estimable Functions |
|
Specifies a list of values to divide the coefficients |
|
Suppresses the automatic fill-in of coefficients for higher-order effects |
|
Tunes the estimability checking difference |
|
Degrees of Freedom and p-values |
|
Determines the method for multiple comparison adjustment of estimates |
|
Determines the confidence level () |
|
Performs one-sided, lower-tailed inference |
|
Adjusts multiplicity-corrected p-values further in a step-down fashion |
|
Specifies values under the null hypothesis for tests |
|
Performs one-sided, upper-tailed inference |
|
Statistical Output |
|
Constructs confidence limits |
|
Displays the correlation matrix of estimates |
|
Displays the covariance matrix of estimates |
|
Prints the matrix |
|
Produces a joint or chi-square test for the estimable functions |
|
Requests ODS statistical graphics if the analysis is sampling-based |
|
Specifies the seed for computations that depend on random numbers |
|
Generalized Linear Modeling |
|
Specifies how to construct estimable functions with multinomial data |
|
Exponentiates and displays estimates |
|
Computes and displays estimates and standard errors on the inverse linked scale |
For details about the syntax of the ESTIMATE statement, see the section ESTIMATE Statement of Chapter 19, Shared Concepts and Topics.
Copyright © SAS Institute, Inc. All Rights Reserved.