• Displays asymptotic correlation matrix of covariance parameter estimates. It is computed from the corresponding asymptotic covariance matrix (see the description of the ASYCOV option, below)
• This option requests that the asymptotic covariance matrix of the covariance parameters be displayed. By default, this matrix is the observed inverse Fisher information matrix, which equals 2H-1, where H is the Hessian (second derivative) matrix of the objective function.
• Displays asymptotic standard errors and Wald tests for covariance parameters
• Computes the estimated variance-covariance matrix of the fixed-effects parameters by using the asymptotically consistent (or sandwich) estimator.
• Displays additional tables of model, dimensional and other information.
• Note: This option was designed for use with analyses requiring extensive CPU resources.
• When you select this option, an analysis of variance table is included in the output, and the expected mean squares are used to estimate the variance components. (See The GLM Procedure for further explanation.)The resulting method-of-moment variance component estimates are used in subsequent calculations, including Type 1 standard errors computed from ESTIMATE and LSMEANS statements.
• Note: This option applies only to variance component models with no SUBJECT= effects and no REPEATED statement.
• When you select this option, an analysis of variance table is included in the output, and the expected mean squares are used to estimate the variance components. (See The GLM Procedure for further explanation.) The resulting method-of-moment variance component estimates are used in subsequent calculations, including Type 2 standard errors computed from ESTIMATE and LSMEANS statements.
• Note: This option applies only to variance component models with no SUBJECT= effects and no REPEATED statement.
• When you select this option, an analysis of variance table is included in the output, and the expected mean squares are used to estimate the variance components. (See The GLM Procedure for further explanation.) The resulting method-of-moment variance component estimates are used in subsequent calculations, including Type 3 standard errors computed from ESTIMATE and LSMEANS statements.
• Note: This option applies only to variance component models with no SUBJECT= effects and no REPEATED statement.
• Requests that coefficients of the mixed model equations be displayed.
• See Estimating in the Mixed Model for more information.
• See Estimating in the Mixed Model for more information.
• For example, variance components have a default lower boundary constraint of 0, and the NOBOUND option allows their estimates to be negative.
• Suppresses the display of the Class Level Information table if you do not specify number.
• Suppresses the display of the Iteration History table.
• Displays ordinates of the relevant distribution in addition to p-values. The ordinate can be viewed as an approximate odds ratio of hypothesis probabilities.
To specify more than one option, press as you left-click on the desired options.Refer to the SAS documentation for PROC MIXED for more information.