The SURVEYPHREG Procedure

LSMEANS Statement

LSMEANS <model-effects> </ options> ;

The LSMEANS statement computes and compares least squares means (LS-means) of fixed effects. LS-means are predicted population margins—that is, they estimate the marginal means over a balanced population. In a sense, LS-means are to unbalanced designs as class and subclass arithmetic means are to balanced designs.

Table 93.4 summarizes the options available in the LSMEANS statement.

Table 93.4: LSMEANS Statement Options

Option	Description
Construction and Computation of LS-Means
AT	Modifies the covariate value in computing LS-means
BYLEVEL	Computes separate margins
DIFF	Requests differences of LS-means
OM=	Specifies the weighting scheme for LS-means computation as determined by the input 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 ( $1-\alpha$ )
STEPDOWN	Adjusts multiple-comparison p-values further in a step-down fashion
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
LINES	Produces a “Lines” display for pairwise LS-means differences
MEANS	Prints the LS-means
PLOTS=	Requests graphs of means and mean comparisons
SEED=	Specifies the seed for computations that depend on random numbers

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