The MODEL statement names a single dependent variable and the fixed effects, which determine the matrix of the mixed model. The MODEL statement is required.
An intercept is included in the fixed-effects model by default. If no fixed effects are specified, only this intercept term is fit. The intercept can be removed by using the NOINT option.
Table 10.5 summarizes options in the MODEL statement. These are subsequently discussed in detail in alphabetical order.
Table 10.5: Summary of Important MODEL Statement Options
You can specify the following options in the MODEL statement after a slash (/).
ALPHA=
sets the confidence level to be for each confidence interval of the fixed-effects parameters, where must be a number between 0 and 1. By default, ALPHA=0.05.
CL
constructs that t-type confidence limits for each of the fixed-effects parameter estimates. The confidence level is 0.95 by default; this can be changed by specifying the ALPHA= option.
DDFM=NONE | RESIDUAL
specifies the method for computing the denominator degrees of freedom for the tests of fixed effects.
NONE
does not apply any denominator degrees of freedom. PROC LMIXED then essentially assumes that infinite degrees of freedom are available in the calculation of p-values. The p-values for t tests are then identical to p-values that are derived from the standard normal distribution.
RESIDUAL
performs all tests by using the residual degrees of freedom, , where n is the number of observations used.
By default, DDFM=RESIDUAL.
NOINT
requests that no intercept be included in the model. (An intercept is included by default.)
SOLUTION
S
produces a solution for the fixed-effects parameters. Using notation from the section Linear Mixed Models Theory, the fixed-effects parameter estimates are and their approximate standard errors are the square roots of the diagonal elements of .
Along with the estimates and their approximate standard errors, a t statistic is computed as the estimate divided by its standard error. The Pr |t| column contains the two-tailed p-value that corresponds to the t statistic and associated degrees of freedom. You can use the CL option to request confidence intervals for all of the parameters; they are constructed around the estimate by using a radius that is the product of the standard error times a percentage point from the t distribution.