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 16.19 summarizes the options available in the LSMEANS statement.
Table 16.19: 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= |
Determines the confidence level () |
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 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 SAS/STAT 13.2 User's Guide.