SAS/STAT 922 User's Guide: The MIXED Procedure (Book Excerpt)

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4524 ✦ Chapter 56: The MIXED Procedure The “Fit Statistics” table in Figure 56.13 contains basic information about the REML fit. Figure 56.13 Fit Statistics Fit Statistics -2 Res Log Likelihood 71.0 AIC (smaller is better) 77.0 AICC (smaller is better) 79.0 BIC (smaller is better) 75.2 The “Type 3 Tests of Fixed Effects” table in Figure 56.14 contains a significance test for the lone fixed effect, Gender. Note that the associated p-value is not nearly as significant as in the previous analysis. This illustrates the importance of correctly modeling correlation in your data. Figure 56.14 Type 3 Tests of Fixed Effects Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F Gender 1 3 7.95 0.0667 An additional benefit of the random effects analysis is that it enables you to make inferences about gender that apply to an entire population of families, whereas the inferences about gender from the analysis where Family and Family*Gender are fixed effects apply only to the particular families in the data set. PROC MIXED thus offers you the ability to model correlation directly and to make inferences about fixed effects that apply to entire populations of random effects.
Syntax: MIXED Procedure The following statements are available in PROC MIXED. PROC MIXED < options > ; BY variables ; CLASS variables ; ID variables ; MODEL dependent = < fixed-effects > < / options > ; RANDOM random-effects < / options > ; REPEATED < repeated-effect >< / options > ; PARMS (value-list) . . . < / options > ; PRIOR < distribution >< / options > ; CONTRAST ’label’ < fixed-effect values . . . > < | random-effect values . . . >, . . . < / options > ; ESTIMATE ’label’ < fixed-effect values . . . > < | random-effect values . . . >< / options > ; LSMEANS fixed-effects < / options > ; LSMESTIMATE model-effect lsmestimate-specification < / options > ; SLICE model-effect < / options > ; STORE < OUT= >item-store-name < / LABEL=‘label’ > ; WEIGHT variable ; Syntax: MIXED Procedure ✦ 4525 Items within angle brackets ( < > ) are optional. The CONTRAST, ESTIMATE, LSMEANS, and RANDOM statements can appear multiple times; all other statements can appear only once. The PROC MIXED and MODEL statements are required, and the MODEL statement must appear after the CLASS statement if a CLASS statement is included. The CONTRAST, ESTI- MATE, LSMEANS, RANDOM, and REPEATED statements must follow the MODEL statement. The CONTRAST and ESTIMATE statements must also follow any RANDOM statements. The LSMESTIMATE, SLICE, and STORE statements are shared with many procedures. Summary descriptions of functionality and syntax for these statements are also given after the PROC MIXED statement in alphabetical order, but you can find full documentation on them in Chapter 19, “Shared Concepts and Topics.” Table 56.1 summarizes the basic functions and important options of each PROC MIXED statement. The syntax of each statement in Table 56.1 is described in the following sections in alphabetical order after the description of the PROC MIXED statement. Table 56.1 Summary of PROC MIXED Statements Statement Description Important Options PROC MIXED Invokes the procedure DATA= specifies input data set, METHOD= specifies estimation method BY Performs multiple PROC MIXED analyses in one invocation None
Page 1 and 2: SAS/STAT ® 9.22 User’s Guide The
Page 3 and 4: Chapter 56 The MIXED Procedure Cont
Page 5 and 6: Basic Features ✦ 4515 Repeated me
Page 7 and 8: PROC MIXED Contrasted with Other SA
Page 9 and 10: proc mixed data=heights; class Fami
Page 11 and 12: Figure 56.6 Fit Statistics Fit Stat
Page 13: Figure 56.10 Dimensions and Number
Page 17 and 18: Table 56.1 continued Statement Desc
Page 19 and 20: PROC MIXED Statement ✦ 4529 CL< =
Page 21 and 22: INFO PROC MIXED Statement ✦ 4531
Page 23 and 24: ORD PROC MIXED Statement ✦ 4533 d
Page 25 and 26: PROC MIXED Statement ✦ 4535 RESID
Page 27 and 28: PROC MIXED Statement ✦ 4537 RANDO
Page 29 and 30: CLASS Statement ✦ 4539 Because so
Page 31 and 32: contrast 'A narrow' A 1 -1 0 A*B .5
Page 33 and 34: ESTIMATE Statement ESTIMATE ’labe
Page 35 and 36: ID Statement ID variables ; ID Stat
Page 37 and 38: ADJUST=BON proc mixed; class A; mod
Page 39 and 40: LSMEANS Statement ✦ 4549 BYLEVEL
Page 41 and 42: SLICE= fixed-effect LSMESTIMATE Sta
Page 43 and 44: Table 56.6 Summary of Important MOD
Page 45 and 46: MODEL Statement ✦ 4555 DDFM=KENWA
Page 47 and 48: E E1 E2 E3 MODEL Statement ✦ 4557
Page 49 and 50: Table 56.8 continued Description Su
Page 51 and 52: SIZE=n MODEL Statement ✦ 4561 If
Page 53 and 54: MODEL Statement ✦ 4563 Table 56.1
Page 55 and 56: The estimated prediction variance i
Page 57 and 58: PARMS Statement PARMS (value-list)
Page 59 and 60: OLS PRIOR Statement ✦ 4569 By def
Page 61 and 62: PRIOR Statement ✦ 4571 JEFFREYS s
Page 63 and 64: RANDOM Statement ✦ 4573 TDATA= en
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RANDOM Statement ✦ 4575 GCORR dis
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RANDOM Statement ✦ 4577 component
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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 ✦ 4583 assumed
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REPEATED Statement ✦ 4585 functio
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REPEATED Statement ✦ 4587 The fol
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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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WEIGHT Statement WEIGHT variable ;
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Example: Growth Curve with Compound
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Mixed Models Theory ✦ 4597 Such a
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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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Estimating Fixed and Random Effects
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Inference and Test Statistics Mixed
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Mixed Models Theory ✦ 4605 (2002,
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Intercept Parameterization of Mixed
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Table 56.18 continued Data I A B(A)
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Residuals and Influence Diagnostics
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Scaled Residuals Residuals and Infl
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Predicted Values, PRESS Residual, a
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When ITER=0 and 2 is profiled, then
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Using results in Cook and Weisberg
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Default Output ✦ 4621 The Evaluat
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Null Model Likelihood Ratio Test De
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Table 56.22 continued ODS Table Nam
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ODS Table Names ✦ 4627 CAUTION: T
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ODS Graphics ✦ 4629 Some of the v
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Figure 56.16 Panel of the Condition
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Figure 56.18 Deletion Estimates ODS
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Computational Issues Computational
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Memory Computational Issues ✦ 463
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Examples: MIXED Procedure Examples:
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Example 56.1: Split-Plot Design ✦
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Example 56.1: Split-Plot Design ✦
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4 F 23.5 24.5 25.0 26.5 5 F 21.5 23
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Output 56.2.4 Repeated Measures Ana
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Output 56.2.7 Repeated Measures Ana
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Example 56.2: Repeated Measures ✦
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Output 56.2.14 Analysis with Compou
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Example 56.2: Repeated Measures ✦
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Example 56.3: Plotting the Likeliho
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Output 56.3.3 continued Number of O
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Output 56.3.8 Fit Statistics and Li
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Output 56.3.12 Least Squares Means
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Both G and R are known. 2 2 1 1 2 1
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Output 56.4.2 Model Dimensions and
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Example 56.4: Known G and R ✦ 466
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Example 56.5: Random Coefficients
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Example 56.5: Random Coefficients
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Output 56.5.7 Random Coefficients A
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Output 56.5.10 continued Covariance
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Example 56.6: Line-Source Sprinkler
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Output 56.6.3 Model Dimensions and
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Example 56.6: Line-Source Sprinkler
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Example 56.7: Influence in Heteroge
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Example 56.7: Influence in Heteroge
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Output 56.7.5 Covariance Parameter
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Output 56.7.7 Restricted Likelihood
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Output 56.7.9 Covariance Parameter
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Example 56.8: Influence Analysis fo
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Output 56.8.2 Restricted Likelihood
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Page 191 and 192:
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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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Output 56.10.1 Analysis of LS-Means
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References ✦ 4711 Cook, R. D. (19
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References ✦ 4713 Harville, D. A.
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References ✦ 4715 Matérn, B. (19
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Bulletin No. 343, Louisiana Agricul
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Subject Index 2D geometric anisotro
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graphics, influence diagnostics, 46
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matrix notation, theory (MIXED), 45
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parameter constraints, 4568, 4636 p
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subject effect MIXED procedure, 454
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INFLUENCE option, MODEL statement (
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NSAMPLE= option, 4572 NSEARCH= opti
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ESTIMATE statement (MIXED), 4544 LS
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SAS® Publishing Delivers! Whether
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SAS/STAT 922 User's Guide: The MIXED Procedure (Book Excerpt)

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