The SURVEYLOGISTIC Procedure

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.