Imbalance or incomplete data, SASophylistic view [🇷 for BE/BA]
Dear Yung-yin,
here comes the incomplete data
As you see, there is no such thing like the ANOVA table in Proc MIXED.
here comes the incomplete data
The GLM Procedure
Dependent Variable: logCmax
Sum of
Source DF Squares Mean Square F Value Pr > F
Model 25 5.38508084 0.21540323 5.28 0.0001
Error 21 0.85689625 0.04080458
Corrected Total 46 6.24197709
The GLM Procedure
Tests of Hypotheses for Mixed Model Analysis of Variance
Dependent Variable: logCmax
Source DF Type III SS Mean Square F Value Pr > F
formul 1 0.010764 0.010764 0.26 0.6129
period 1 0.004803 0.004803 0.12 0.7349
Subject(Sequence) 22 5.162645 0.234666 5.75 <.0001
Error: MS(Error) 21 0.856896 0.040805
Source DF Type III SS Mean Square F Value Pr > F
Sequence 1 0.250808 0.250808 1.09 0.3082
Error 22.166 5.110348 0.230549
Error: 0.9788*MS(Subject(Sequence)) + 0.0212*MS(Error)
The Mixed Procedure
Model Information
Data Set WORK.BEBAC24LONG
Dependent Variable logCmax
Covariance Structure Variance Components
Subject Effect Subject
Estimation Method REML
Residual Variance Method Profile
Fixed Effects SE Method Model-Based
Degrees of Freedom Method Satterthwaite
Class Level Information
Class Levels Values
formul 2 R T
period 2 1 2
Subject 24 1 2 3 4 5 6 7 8 9 10 11 12 13
14 15 16 17 18 19 20 21 22 23
24
Sequence 2 RT TR
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
0 1 48.72149331
1 2 34.40082009 0.00001350
2 1 34.40051663 0.00000000
The Mixed Procedure
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm Subject Estimate
Subject(Sequence) Subject 0.1002
Residual 0.04102
Fit Statistics
-2 Res Log Likelihood 34.4
AIC (smaller is better) 38.4
AICC (smaller is better) 38.7
BIC (smaller is better) 40.8
Type 3 Tests of Fixed Effects
Num Den
Effect DF DF F Value Pr > F
formul 1 21.1 0.38 0.5422
period 1 21.1 0.06 0.8145
Sequence 1 21.8 0.99 0.3309
Least Squares Means
Standard
Effect formul Estimate Error DF t Value Pr > |t| Alpha Lower Upper
formul R 3.4844 0.07757 29.6 44.92 <.0001 0.1 3.3527 3.6161
formul T 3.4475 0.07671 28.8 44.94 <.0001 0.1 3.3171 3.5779
Differences of Least Squares Means
Standard
Effect formul _formul Estimate Error DF t Value Pr > |t| Alpha
formul R T 0.03692 0.05959 21.1 0.62 0.5422 0.1
Differences of Least Squares Means
Effect formul _formul Lower Upper
formul R T -0.06561 0.1394
As you see, there is no such thing like the ANOVA table in Proc MIXED.
—
Regards,
Detlew
Regards,
Detlew
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