f2 - Iteration Evaluations-2 Res Log Like Criterion 0 1...

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Example F2 SAS Program data hogs; input litter gain; datalines ; 1 1.18 1 1.11 2 1.36 2 1.65 3 1.37 3 1.40 4 1.07 4 0.90 ; run ; proc mixed data =hogs cl ; class litter ; model gain = ; random litter/ solution ; estimate 'Litter 1 Effect' | litter 1 0 0 0 ; estimate 'Litter 2 Effect' | litter 0 1 0 0 ; estimate 'Litter 3 Effect' | litter 0 0 1 0 ; estimate 'Litter 4 Effect' | litter 0 0 0 1 ; title 'Average Daily Gain in Swine' ; run ;
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Average Daily Gain in Swine 1 The Mixed Procedure Model Information Data Set WORK.HOGS Dependent Variable gain Covariance Structure Variance Components Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Containment Class Level Information Class Levels Values litter 4 1 2 3 4 Dimensions Covariance Parameters 2 Columns in X 1 Columns in Z 4 Subjects 1 Max Obs Per Subject 8 Number of Observations Number of Observations Read 8 Number of Observations Used 8 Number of Observations Not Used 0
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Iteration History
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Unformatted text preview: Iteration Evaluations -2 Res Log Like Criterion 0 1 1.69956771 1 1 -1.52719436 0.00000000 Convergence criteria met. Average Daily Gain in Swine 2 The Mixed Procedure Covariance Parameter Estimates Cov Parm Estimate Alpha Lower Upper litter 0.04738 0.05 0.01341 1.3843 Residual 0.01485 0.05 0.005331 0.1226 Fit Statistics -2 Res Log Likelihood -1.5 AIC (smaller is better) 2.5 AICC (smaller is better) 5.5 BIC (smaller is better) 1.2 Solution for Random Effects Std Err Effect litter Estimate Pred DF t Value Pr > |t| litter 1 -0.09510 0.1291 4 -0.74 0.5021 litter 2 0.2161 0.1291 4 1.67 0.1693 litter 3 0.1124 0.1291 4 0.87 0.4330 litter 4 -0.2334 0.1291 4 -1.81 0.1448 Estimates Standard Label Estimate Error DF t Value Pr > |t| Litter 1 Effect -0.09510 0.1291 4 -0.74 0.5021 Litter 2 Effect 0.2161 0.1291 4 1.67 0.1693 Litter 3 Effect 0.1124 0.1291 4 0.87 0.4330 Litter 4 Effect -0.2334 0.1291 4 -1.81 0.1448...
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f2 - Iteration Evaluations-2 Res Log Like Criterion 0 1...

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