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Example^ F14 SAS Programdata^ pigs;input^ sire dam @;do^ rep=^1 to^^2 ; input^ gain @;output;end;datalines; 1 1 2.77 2.38 1 2 2.58 2.94 2 1 2.28 2.22 2 2 3.01 2.61 3 1 2.36 2.71 3 2 2.72 2.74 4 1 2.87 2.46 4 2 2.31 2.24 5 1 2.74 2.56 5 2 2.50 2.48; run ; proc^ glm^ data=pigs;class^ sire dam;model^ gain = sire dam(sire);random^ dam(sire)/test;lsmeans^ sire/stderr;lsmeans^ sire/stderr
e=dam(sire);
title^ 'Analysis of Average Daily Gain using PROC GLM'; run ; ---------------------------------------------------------------------------------------------------------------------------------------------------------------------
Proc Mixed Analysisproc^ mixed^ data=pigs noclprint
noinfo^ cl;;
class^ sire dam;model^ gain = sire/ddfm=satterth;random^ dam(sire);lsmeans^ sire;estimate^ 'Sire 1 BLUE'intercept
^1 sire^^1 0 0 0 0 ;
estimate^ 'Sire 1 BLUP'intercept
^2 sire 2 0 0 0 0 | dam(sire)^^1 1 0 0 0 0
0 0 0 /divisor=^2 cl;
title^ 'Analysis of Average Daily Gain using PROC MIXED'; run ;
Analysis of Average^ Daily Gain
using^ PROC GLM^
The^ GLM Procedure Dependent Variable: gain
Sum of Source^
DF^ Squares^ Mean
Square^ F^ Value^ Pr >
F
Model^
9 0.66328000^ 0.
1.90^ 0.
Error^
10 0.^
Corrected^ Total^
19 1.05028000R-Square Coeff^ Var^ Root^ MSE
gain^ Mean 0.631527^ 7.
0.196723^ 2.
Source^
DF^ Type^ I SS^ Mean
Square^ F^ Value^ Pr >
F
sire^
4 0.09973000^ 0.
0.64^ 0.
dam(sire)^
5 0.56355000^ 0.
2.91^ 0.
Source^
DF^ Type III SS^ Mean
Square^ F^ Value^ Pr >
F
sire^
4 0.09973000^ 0.
0.64^ 0.
dam(sire)^
5 0.56355000^ 0.
2.91^ 0.
Analysis of Average^ Daily Gain
using^ PROC GLM^
The^ GLM Procedure Source^
Type^ III Expected^ Mean Square sire^
Var(Error)^ + 2^ Var(dam(sire))
Var(Error)^ + 2^ Var(dam(sire))Analysis of Average^ Daily Gain^ using
PROC GLM^
The^ GLM ProcedureTests of Hypotheses for Mixed^ Model^ Analysis
of Variance Dependent Variable: gainSource^
DF^ Type III SS^ Mean
Square^ F^ Value^ Pr >
F
sire^
4 0.^
0.024932^ 0.22^ 0.
Error:^ MS(dam(sire))^
5 0.^
Source^
DF^ Type III SS^ Mean
Square^ F^ Value^ Pr >
F
dam(sire)^
5 0.^
0.112710^ 2.91^ 0.
Error:^ MS(Error)^
10 0.^
Proc MIXED Output^ Analysis
of^ Average Daily^ Gain
using PROC^ MIXED^
The^ Mixed ProcedureIteration^ HistoryIteration Evaluations^ -2^ Res^ Log Like
Criterion 0 1
6.06578536^ 0.00000000Convergence criteria^ met.Covariance Parameter Estimates Cov Parm^ Estimate
Alpha^ Lower
Upper dam(sire)^ 0.
0.05^ 0.
Residual^ 0.
0.05^ 0.
Fit Statistics-2 Res Log Likelihood^
AIC^ (smaller^ is^ better)
AICC (smaller^ is^ better)
BIC^ (smaller^ is^ better)
10.7 Type 3 Tests of Fixed^ EffectsNum Den Effect^ DF^
DF^ F^ Value^ Pr >^
F
sire^4
5 0.22^ 0.
EstimatesStandard Label^ Estimate
Error^ DF^
t^ Value^ Pr >^ |t|^
Alpha
Sire^ 1 BLUE^ 2.
0.1679^5
15.89^ <.^
Sire^ 1 BLUP^ 2.
0.09836^10
27.12^ <.^
Analysis^ of^ Average Daily
Gain^ using PROC^ MIXED
The^ Mixed ProcedureEstimatesLabel Lower^
Upper Sire^ 1 BLUE^ 2.
Sire^ 1 BLUP^ 2.
2.8867 Least Squares MeansStandard Effect^ sire^ Estimate
Error^ DF^
t^ Value^ Pr >^ |t| sire^1 2.
0.1679^5
15.89^ <.
sire^2 2.
0.1679^5
15.07^ <.
sire^3 2.
0.1679^5
15.68^ <.
sire^4 2.
0.1679^5
14.71^ <.
sire^5 2.
0.1679^5
15.31^ <.
