The SURVEYLOGISTIC Procedure

LSMESTIMATE Statement

LSMESTIMATE model-effect <'label'> values <divisor=n> <, …<'label'> values <divisor=n>></ options> ;

The LSMESTIMATE statement provides a mechanism for obtaining custom hypothesis tests among least squares means.

Table 91.6 summarizes the options available in the LSMESTIMATE statement.

Table 91.6: LSMESTIMATE Statement Options

Option

Description

Construction and Computation of LS-Means

AT

Modifies covariate values in computing LS-means

BYLEVEL

Computes separate margins

DIVISOR=

Specifies a list of values to divide the coefficients

OM=

Specifies the weighting scheme for LS-means computation as determined by a data set

SINGULAR=

Tunes estimability checking

Degrees of Freedom and p-values

ADJUST=

Determines the method for multiple-comparison adjustment of LS-means differences

ALPHA=$\alpha $

Determines the confidence level ($1-\alpha $)

LOWER

Performs one-sided, lower-tailed inference

STEPDOWN

Adjusts multiple-comparison p-values further in a step-down fashion

TESTVALUE=

Specifies values under the null hypothesis for tests

UPPER

Performs one-sided, upper-tailed inference

Statistical Output

CL

Constructs confidence limits for means and mean differences

CORR

Displays the correlation matrix of LS-means

COV

Displays the covariance matrix of LS-means

E

Prints the $\mb {L}$ matrix

ELSM

Prints the $\mb {K}$ matrix

JOINT

Produces a joint F or chi-square test for the LS-means and LS-means differences

SEED=

Specifies the seed for computations that depend on random numbers

Generalized Linear Modeling

CATEGORY=

Specifies how to construct estimable functions with multinomial data

EXP

Exponentiates and displays LS-means estimates

ILINK

Computes and displays estimates and standard errors of LS-means (but not differences) on the inverse linked scale


For details about the syntax of the LSMESTIMATE statement, see the section LSMESTIMATE Statement in Chapter 19: Shared Concepts and Topics.