The LSMEANS statement 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 73.8 summarizes the options available in the LSMEANS statement. If the BAYES statement is specified, the ADJUST=, STEPDOWN, and LINES options are ignored. The PLOTS= option is not available for the maximum likelihood analysis. It is available only for the Bayesian analysis.
Table 73.8: LSMEANS Statement Options
Option |
Description |
---|---|
Construction and Computation of LS-Means |
|
Modifies the covariate value in computing LS-means |
|
Computes separate margins |
|
Requests differences of LS-means |
|
Specifies the weighting scheme for LS-means computation as determined by the input data set |
|
Tunes estimability checking |
|
Degrees of Freedom and p-values |
|
Determines the method for multiple-comparison adjustment of LS-means differences |
|
Determines the confidence level () |
|
Adjusts multiple-comparison p-values further in a step-down fashion |
|
Statistical Output |
|
Constructs confidence limits for means and mean differences |
|
Displays the correlation matrix of LS-means |
|
Displays the covariance matrix of LS-means |
|
Prints the matrix |
|
Produces a "Lines" display for pairwise LS-means differences |
|
Prints the LS-means |
|
Requests graphs of means and mean comparisons |
|
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.