SAS/STAT 9.2 User's Guide: The MIXED Procedure (Book Excerpt)

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4022 ✦ Chapter 56: The MIXED Procedure Output 56.2.14 Analysis with Compound Symmetry (continued) Covariance Parameter Estimates Standard Z Cov Parm Subject Estimate Error Value Pr Z CS Person 3.0306 0.9552 3.17 0.0015 Residual 1.8746 0.2946 6.36 ChiSq 1 49.60 |t| Intercept 16.3406 0.9631 25 16.97
Output 56.2.17 Analysis with Compound Symmetry (continued) Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F Gender 1 25 0.47 0.5003 Age 1 79 111.10
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SAS/STAT ® 9.2 User’s Guide The
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Chapter 56 The MIXED Procedure Cont
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Basic Features ✦ 3887 clustered i
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variance components compound symmet
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Clustered Data Example ✦ 3891 The
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Clustered Data Example ✦ 3893 mat
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criterion of 1E 8. Figure 56.11 REM
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Syntax: MIXED Procedure ✦ 3897 Th
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Table 56.2 continued Option Descrip
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If H k is singular, then PROC MIXED
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MMEQ PROC MIXED Statement ✦ 3903
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PLOTS < (global-plot-options ) > <
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Residual Plot Options PROC MIXED St
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RATIO Multiple Plot Request PROC MI
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CONTRAST Statement ✦ 3911 TRUNCAT
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CONTRAST Statement ✦ 3913 differe
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ESTIMATE Statement ✦ 3915 ALPHA=n
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Table 56.5 Summary of Important LSM
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LSMEANS Statement ✦ 3919 The numb
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E LSMEANS Statement ✦ 3921 are di
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Table 56.6 continued Option Descrip
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Table 56.7 Aliases for DDFM= Option
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E E1 E2 E3 FULLX MODEL Statement
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MODEL Statement ✦ 3929 The modifi
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SIZE=n MODEL Statement ✦ 3931 ins
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Table 56.10 continued Suboption Sta
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MODEL Statement ✦ 3935 where Vm i
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PARMS Statement PARMS (value-list)
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OLS PRIOR Statement ✦ 3939 approp
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PRIOR Statement ✦ 3941 JEFFREYS s
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RANDOM Statement ✦ 3943 TDATA= en
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RANDOM Statement ✦ 3945 GCORR dis
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RANDOM Statement ✦ 3947 available
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Table 56.12 continued Option Descri
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proc mixed; class a; model y = a x;
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REPEATED Statement ✦ 3953 TYPE=co
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Table 56.15 Covariance Structure Ex
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REPEATED Statement ✦ 3957 TYPE=AR
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TYPE=SP(EXPGA)(c1 c2) TYPE=SP(GAUGA
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TYPE=UN@AR(1) TYPE=UN@CS REPEATED S
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Mixed Models Theory ✦ 3963 where
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proc mixed; class indiv; model y =
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2 6 Z D 6 4 2 6 G D 6 4 1 1 1 1 1 1
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Mixed Models Theory ✦ 3969 In man
Page 89 and 90: Mixed Models Theory ✦ 3971 Finall
Page 91 and 92: Mixed Models Theory ✦ 3973 When L
Page 93 and 94: Parameterization of Mixed Models
Page 95 and 96: Interaction Effects Parameterizatio
Page 97 and 98: Table 56.20 Example of Continuous-b
Page 99 and 100: as ei ei p D pvi VarŒei and studen
Page 101 and 102: Residuals and Influence Diagnostics
Page 107 and 108: Default Output Default Output ✦ 3
Page 109 and 110: Default Output ✦ 3991 batch proce
Page 111 and 112: ODS Table Names ✦ 3993 You can us
Page 113 and 114: Table 56.22 continued ODS Table Nam
Page 115 and 116: Table 56.23 continued Table Name Va
Page 117 and 118: ODS Graphics ✦ 3999 The graphical
Page 119 and 120: ODS Graphics ✦ 4001 precision is
Page 121 and 122: Table 56.24 continued ODS Graph Nam
Page 123 and 124: Computational Issues ✦ 4005 For f
Page 125 and 126: Memory Computational Issues ✦ 400
Page 127 and 128: The following statements fit the sp
Page 129 and 130: Output 56.1.6 Split-Plot Analysis (
Page 131 and 132: proc mixed; class A B Block; model
Page 133 and 134: Example 56.2: Repeated Measures ✦
Page 135 and 136: Output 56.2.6 Repeated Measures Ana
Page 137 and 138: Output 56.2.9 Repeated Measures Ana
Page 139: Output 56.2.11 continued Dimensions
Page 143 and 144: Example 56.2: Repeated Measures ✦
Page 145 and 146: The results from this analysis are
Page 147 and 148: Output 56.3.6 Estimated Covariance
Page 149 and 150: Output 56.3.10 Solutions of the Mix
Page 151 and 152: Output 56.3.14 Plot of Likelihood S
Page 153 and 154: Example 56.4: Known G and R ✦ 403
Page 155 and 156: Example 56.4: Known G and R ✦ 403
Page 157 and 158: Output 56.4.9 Solutions of the Mixe
Page 159 and 160: Example 56.5: Random Coefficients E
Page 161 and 162: Output 56.5.3 continued Number of O
Page 163 and 164: Output 56.5.9 Random Coefficients A
Page 165 and 166: Example 56.5: Random Coefficients
Page 167 and 168: Example 56.6: Line-Source Sprinkler
Page 169 and 170: Output 56.6.3 Model Dimensions and
Page 171 and 172: Example 56.6: Line-Source Sprinkler
Page 173 and 174: Example 56.7: Influence in Heteroge
Page 175 and 176: Example 56.7: Influence in Heteroge
Page 177 and 178: Output 56.7.5 Covariance Parameter
Page 179 and 180: Output 56.7.7 Restricted Likelihood
Page 181 and 182: Output 56.7.9 Covariance Parameter
Page 183 and 184: Example 56.8: Influence Analysis fo
Page 185 and 186: Output 56.8.2 Restricted Likelihood
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Output 56.8.8 Distribution of Condi
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Output 56.9.2 Type 3 Tests in Split
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Output 56.9.5 Parameter Estimates i
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References ✦ 4079 Carroll, R. J.
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References ✦ 4081 Hanks, R.J., Si
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References ✦ 4083 Littell, R. C.,
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References ✦ 4085 Smith, A. F. M.
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Subject Index 2D geometric anisotro
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graphics, residual panel, 3998 grap
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maximum likelihood estimation mixed
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parameterization, 3975 Pearson resi
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subject effect MIXED procedure, 391
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INFLUENCE option, MODEL statement (
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OUTG= option, 3942 OUTGT= option, 3
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INFLUENCE option, MODEL statement (
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