17. Example SAS Commands for Analysis of a Classic Split-Plot Experiment 17. 1
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1 17 Example SAS Commands for Analysis of a Classic SplitPlot Experiment 17 1
2 DELIMITED options nocenter nonumber nodate ls80; Format SCREEN OUTPUT proc import datafile"c:\data\simulatedsplitplotdatatxt" dbmstab replace outd; READ TAB run; d INTO SAS TEXT FILE DATASET proc print datad (obs14); run; PRINT FIRST 14 Rows OF d To SCREEN ods listing close; TURN OFF options orientationlandscape; ods pdf file"c:\sasoutputpdf" notoc; NO TABLE of contents ) OUTPUT To SCREEN WRITE OUTPUT To A PDF FILE 17 2
3 proc mixed; DEFINE E ( ) > E ( Yi ; k ) µ Xi t Pj 8 is Mij class block geno fert; at model ygeno fert geno*fert / ddfmsatterthwaite; METHOD random block block*geno; DENOMINATOR DEGREES OF FREEDOM estimate 'geno 1' is#moimenyiiiaiwmiiionnayotfhjz AT 1 intercept 4 geno fert geno*fert / divisor4 cl; n t Miz Mi } Mi U 4 µ 4L ' 4) / 4 j Pi ( M x p ; Pz As BY 8 " kz Vis 814 Kj ) < 4 µ a F VT 17 3
4 as Fz ( xz K M NTZ ty Y ( tttditpj Kj ) estimate 'geno 1 geno 2' geno yt 4 ( 8 ; geno*fert / divisor4 cl; 4 L 4 yt Lz ] 4 4 Jiy ( Mt a [ p; 82 ;) Jzz ;) Vzstzy d F estimate 'geno 1 geno 2 with no fertilizer' geno geno*fert / cl; run; µz µ 2 B 8 M xztp µ 8zD L 22 Ji
5 The SAS System Model Information Data Set Dependent Variable Covariance Structure Estimation Method Residual Variance Method WORKD y Variance Components REML Profile Fixed Effects SE Method ModelBased Degrees of Freedom Method Satterthwaite Class Level Information Class Levels Values block geno fert Dimensions Covariance Parameters 3 Columns in X 20 Columns in Z 16 Subjects 1 Max Obs per Subject 48 Number of Observations # Number of Observations Read 48 Number of Observations Used 48 Number of Observations Not Used 0 y bi bz # MAT CHES OUR DATA WITH GENOTYPES A B AND ( 0303 µ ditz 23 b } by of fi Pz B3 Pt Wi Wiz AND Vii 12 RESPECTIVELY 834 DON'T WORRY ABOUT THIS For Now REASON WILL BECOME CLEAR WHEN WE Discuss REPEATED MEASURES ANALYSIS N 48 ( 4 Blocks 3 GENOTYPES 4 Fertilizer AMOUNTS ) 17 5
6 NT3 ( The SAS System Iteration History Iteration Evaluations 2 Res Log Like Criterion Convergence criteria met Covariance Parameter Estimates Cov Parm Estimate block block*geno Residual x Ob / AZ Ow a 2 oe Fit Statistics 2 Res Log Likelihood 2751 AIC (Smaller is Better) 2811 AICC (Smaller is Better) 2818 BIC (Smaller is Better) 2792 Effect Type 3 Tests of Fixed Effects Num DF Den DF F Value Pr > F geno fert <0001 geno*fert µ Ho Ho : TU : AT i Ho : Mi ; ttz It z III / ( No GEWO F No Genotype MAIN Effects ) II 3154 ( No Fert MAIN Effects ) ; t II 0 H i FEKT INTERACTIONS) SAS AUTOMATICALLY Ho REJECTED FOR ALL THREE TESTS Does THESE TESTS CORRECTLY WHETHER DATA ARE BALANCED OR Not j 17 6
7 The SAS System 7 SAS Does THESE TESTS CORRECTLY WHETHER DATA Label Estimate Estimates Standard Error DF tvalue Pr > t Alpha Lower Upper geno < geno 1 geno geno 1 geno 2 with no fertilizer ARE BALANCED OR NOT AND USES SATTERTHWAITE APPROXIMATION WHEN NECESSARY 17 7
8 How Do THINGS CHANGE IF Block EFFECTS ARE Fixed? proc mixed; E(yijk)µt bktditpj Xii class block geno fert; model yblock µi geno MT fert geno*fert / ddfmsatterthwaite; random block*geno; w winyn( 002W) estimate 'geno 1' intercept 4 block geno fert geno*fert / divisor4 cl; estimate 'geno 1 geno 2' geno geno*fert / divisor4 cl; estimate 'geno 1 geno 2 with no fertilizer' geno geno*fert / cl; ods pdf close; ods listing; ( 4 EH ' EM ( Mtbktaitfjtki ) %6 ( 6µ 4bt4bz4bs4b4 16L 4p 4Pa 4p3t4py 4N ( " " " " " " " " " tpitpztpztpyt Jn ) /4 YYIAfm?eonAes BECAUSE BLOCK EFFECTS 17 STOP WRITING OUTPUT To PDF FILE CANCEL START WRITING OUTPUT To SCREEN OUT 17 8
9 The SAS System Model Information Data Set Dependent Variable Covariance Structure Estimation Method Residual Variance Method Fixed Effects SE Method Degrees of Freedom Method WORKD y Variance Components REML Profile ModelBased Satterthwaite Class Level Information Class Levels Values block geno fert gy Dimensions Covariance Parameters 2 Columns in X 24 Columns in Z 12 4 Mor COLUMNS E COLUMNS IN X AND 4 FEWER IN Z BECAUSE b bzb3 by Move To VECTOR From U~ Vector f Subjects 1 Max Obs per Subject 48 Number of Observations Number of Observations Read 48 Number of Observations Used 48 Number of Observations Not Used
10 The SAS System Iteration History Iteration Evaluations 2 Res Log Like Criterion Convergence criteria met Covariance Parameter Estimates Cov Parm Estimate block*geno Residual Fit Statistics 2 Res Log Likelihood 2502 AIC (Smaller is Better) 2542 AICC (Smaller is Better) 2546 BIC (Smaller is Better) 2551 Effect Type 3 Tests of Fixed Effects Num DF X na Den DF F Value Pr > F block geno fert <0001 geno*fert Z D) SAME ] RANDOM As WHEN Block EFFECTS 17 10
11 The SAS System SATTERTHWAITE CONFIDENCE INTERVAL MUCH No LONGER NEEDEDGHERE Estimates Label Estimate Standard Error DF tvalue Pr > t Alpha Lower Upper e geno < geno 1 geno geno 1 geno 2 with no fertilizer ( [ FILET ARE s { Narrower Now THAT BLOCK Considered To SAME As WHEN BLOCK EFFECTS RANDOM BE 17 11
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