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 113.4 summarizes the options available in the LSMEANS statement.

Table 113.4: 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

Generalized Linear Modeling

EXP

Exponentiates and displays estimates of LS-means or LS-means differences

ILINK

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

ODDSRATIO

Reports (simple) differences of least squares means in terms of odds ratios if permitted by the link function


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