I am looking for SAS code to analyze data generated from split-split plot design. Thank you for the support.
There is an example using proc anova
You might be able to adapt this split-split-split example for PROC ANOVA: http://support.sas.com/documentation/onlinedoc/stat/ex_code/132/aovspl3.html
Chris
Thank you all, I will try.
I was wondering if the Example in http://support.sas.com/documentation/onlinedoc/stat/ex_code/132/aovspl3.html can be used for random effects split-split plot models. Specifically, can Proc anova be used for mixed-effects Split-split plot designs? If not, can the same approach be used in Proc Mixed when for instance the subplot factor is considered as random?
You can reproduce the ANOVA results using PROC MIXED by adding the TEST statement E= terms to RANDOM statements in PROC MIXED.
data tires;
   input fabric rubber rep @;
   do cure=1 to 2;
      do temp=1 to 2;
         do piece=1 to 2;
            input y @; output;
            end;
         end;
      end;
   datalines;
1 1  1  29  26  34  29  40  35  76  64
1 1  2  84  54  41  40 136  67  74  58
1 1  3  87  66  47  37  70  56  63  55
1 1  4  80  70  53  27  68  37  49  38
1 1  5  79  48  63  53  66  48  43  29
1 2  1 113  81  88  48  84  37  91  57
1 2  2 108  92  71  49  81  72  55  52
1 2  3 123 108  59  49 121 101  98  42
1 2  4  57  43  47  28 102  56  95  55
1 2  5  82  76  80  35  84  73  50  50
2 1  6   6   6  32  16   7   7  34  22
2 1  7   6   6  26  18  12  12  26  24
2 1  8  12  12  52  20  14  12  41  36
2 1  9   9   6  21  16   9   7  15  14
2 1 10  15  13  21  17  13   9  34  15
2 2  6   6   6  15  12  16   7  41  19
2 2  7   6   6  25  19   8   6  23  23
2 2  8   7   7  50  32  20  19  47  33
2 2  9  13   8  22  20  23  23  64  33
2 2 10   6   6  27  19  16  14  74  31
3 1 11  76  68  34  22  27  20 118  29
3 1 12  16  11  24  15  43  31  49  36
3 1 13  61  50  46  24  36  25  62  21
3 1 14  41  23  29  19  25  13  66  43
3 1 15   8   6  14  11   7   7  28  21
3 2 11  13  11  53  26  37  24  59  52
3 2 12  22  19  22  22  99  17  45  38
3 2 13  22  18  48  18  76  48  30  25
3 2 14  58  32  30  26  72  64  94  43
3 2 15   7   7  11  11  16  12  19  13
;
proc anova;
   classes fabric rubber rep cure temp piece;
   model y=fabric  rep(fabric)
           rubber  rubber*fabric
                   rubber*rep(fabric)
           cure    cure*fabric   cure*rubber
                   cure*rubber*fabric
                   cure*rubber*rep(fabric)
           temp temp*fabric temp*rubber temp*fabric*rubber
                temp*cure temp*cure*fabric temp*cure*rubber
                temp*cure*fabric*rubber
                temp*cure*rubber*rep(fabric);
   test h=fabric e=rep(fabric);
   test h=rubber rubber*fabric e=rubber*rep(fabric);
   test h=cure cure*fabric cure*rubber cure*rubber*fabric
        e=cure*rubber*rep(fabric);
   test h=temp temp*fabric temp*rubber temp*fabric*rubber
          temp*cure temp*cure*fabric temp*cure*rubber
          temp*cure*fabric*rubber
        e=temp*cure*rubber*rep(fabric);
   title 'Split-split-split Plot Design: Tire Experiment';
   run; quit;
proc mixed;
   class fabric rubber rep cure temp piece;
   model y=fabric  /*rep(fabric)*/
           rubber  rubber*fabric
                   /*rubber*rep(fabric)*/
           cure    cure*fabric   cure*rubber
                   cure*rubber*fabric
                   /*cure*rubber*rep(fabric)*/
           temp temp*fabric temp*rubber temp*fabric*rubber
                temp*cure temp*cure*fabric temp*cure*rubber
                temp*cure*fabric*rubber
                /*temp*cure*rubber*rep(fabric)*/;
   random rep(fabric);
   random rubber*rep(fabric);
   random cure*rubber*rep(fabric);
   random temp*cure*rubber*rep(fabric);
   lsmeans rubber*fabric / diff;
   title 'Split-split-split Plot Design: Tire Experiment';
   run; quit;
 
Thank you. I got it like that and it works perfectly well.
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