Output from probe1.sas

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Profile Analysis Example: PROBE1 (Timm, Ex. 3.14) 1

                     SUBJNO    P1    P2    P3    P4    P5
                        1      51    36    50    35    42
                        2      27    20    26    17    27
                        3      37    22    41    37    30
                        4      42    36    32    34    27
                        5      27    18    33    14    29
                        6      43    32    43    35    40
                        7      41    22    36    25    38
                        8      38    21    31    20    16
                        9      36    23    27    25    28
                       10      26    31    31    32    36
                       11      29    20    25    26    25

Profile Analysis Example: PROBE1 (Timm, Ex. 3.14) 2

               Variable  Label               Mean       Std Dev
               ------------------------------------------------
               P1        Position 1    36.0909091     8.0678937
               P2        Position 2    25.5454545     6.7876894
               P3        Position 3    34.0909091     7.7904370
               P4        Position 4    27.2727273     7.9257922
               P5        Position 5    30.7272727     7.6300840
               ------------------------------------------------

Profile Analysis Example: PROBE1 (Timm, Ex. 3.14) 3

          Plot of SPEED1*_NAME_.  Legend: A = 1 obs, B = 2 obs, etc.

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       36 +  A
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       34 +                              A
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     R 32 +
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     e 30 +
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       28 +
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       26 +
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          ---+-------------+-------------+-------------+-------------+--
            P1            P2            P3            P4            P5

                                 Sentence Position


Profile Analysis Example: PROBE1 (Timm, Ex. 3.14) 4 Single Sample Profile Analysis (flat profile)

                       General Linear Models Procedure
                   Number of observations in data set = 11


Profile Analysis Example: PROBE1 (Timm, Ex. 3.14) 5 Single Sample Profile Analysis (flat profile)

                       General Linear Models Procedure
                    Repeated Measures Analysis of Variance
                     Repeated Measures Level Information

      Dependent Variable         P1       P2       P3       P4       P5

       Level of POSITION          1        2        3        4        5


Profile Analysis Example: PROBE1 (Timm, Ex. 3.14) 6 Single Sample Profile Analysis (flat profile)

                       General Linear Models Procedure
                    Repeated Measures Analysis of Variance

  Partial Correlation Coefficients from the Error SS&CP Matrix / Prob > |r|

         DF = 10           P1        P2        P3        P4        P5
         P1          1.000000  0.614390  0.757185  0.575073  0.413057
                       0.0001    0.0443    0.0070    0.0642    0.2067
         P2          0.614390  1.000000  0.547390  0.749777  0.547660
                       0.0443    0.0001    0.0813    0.0079    0.0812
         P3          0.757185  0.547390  1.000000  0.605272  0.691893
                       0.0070    0.0813    0.0001    0.0485    0.0183
         P4          0.575073  0.749777  0.605272  1.000000  0.523888
                       0.0642    0.0079    0.0485    0.0001    0.0981
         P5          0.413057  0.547660  0.691893  0.523888  1.000000
                       0.2067    0.0812    0.0183    0.0981    0.0001



                            E = Error SS&CP Matrix

POSITI.N represents the contrast between the nth level of POSITION and the 5th
                  POSITI.1         POSITI.2         POSITI.3         POSITI.4

 POSITI.1      724.5454545      380.7272727      392.5454545      378.8181818
 POSITI.2      380.7272727      475.6363636      176.7272727      385.0909091
 POSITI.3      392.5454545      176.7272727      366.5454545      227.8181818
 POSITI.4      378.8181818      385.0909091      227.8181818      576.7272727


Profile Analysis Example: PROBE1 (Timm, Ex. 3.14) 7 Single Sample Profile Analysis (flat profile)

                       General Linear Models Procedure
                    Repeated Measures Analysis of Variance

         Partial Correlation Coefficients from the Error SS&CP Matrix
    of the Variables Defined by the Specified Transformation / Prob > |r|
              DF = 10     POSITI.1  POSITI.2  POSITI.3  POSITI.4

              POSITI.1    1.000000  0.648550  0.761716  0.586020
                            0.0001    0.0309    0.0064    0.0581
              POSITI.2    0.648550  1.000000  0.423255  0.735259
                            0.0309    0.0001    0.1946    0.0099
              POSITI.3    0.761716  0.423255  1.000000  0.495495
                            0.0064    0.1946    0.0001    0.1212
              POSITI.4    0.586020  0.735259  0.495495  1.000000
                            0.0581    0.0099    0.1212    0.0001



             Test for Sphericity: Mauchly's Criterion = 0.0879791
  Chisquare Approximation = 20.458026 with 9 df   Prob > Chisquare = 0.0153

                      Applied to Orthogonal Components:
             Test for Sphericity: Mauchly's Criterion = 0.4796455
  Chisquare Approximation = 6.1837927 with 9 df   Prob > Chisquare = 0.7214

                    H = Type III SS&CP Matrix for POSITION
POSITI.N represents the contrast between the nth level of POSITION and the 5th
                  POSITI.1         POSITI.2         POSITI.3         POSITI.4

 POSITI.1     316.45454545     -305.7272727     198.45454545     -203.8181818
 POSITI.2     -305.7272727     295.36363636     -191.7272727     196.90909091
 POSITI.3     198.45454545     -191.7272727     124.45454545     -127.8181818
 POSITI.4     -203.8181818     196.90909091     -127.8181818     131.27272727


               Manova Test Criteria and Exact F Statistics for
                     the Hypothesis of no POSITION Effect
       H = Type III SS&CP Matrix for POSITION   E = Error SS&CP Matrix

Profile Analysis Example: PROBE1 (Timm, Ex. 3.14) 8 Single Sample Profile Analysis (flat profile)

                       General Linear Models Procedure
                    Repeated Measures Analysis of Variance

                             S=1    M=1    N=2.5

 Statistic                     Value          F      Num DF    Den DF  Pr > F
 Wilks' Lambda              0.24822547     5.3000         4         7  0.0277
 Pillai's Trace             0.75177453     5.3000         4         7  0.0277
 Hotelling-Lawley Trace     3.02859542     5.3000         4         7  0.0277
 Roy's Greatest Root        3.02859542     5.3000         4         7  0.0277

Profile Analysis Example: PROBE1 (Timm, Ex. 3.14) 9 Test of sentence structure hypotheses (POSITION contrasts)

                       General Linear Models Procedure
                   Number of observations in data set = 11

Profile Analysis Example: PROBE1 (Timm, Ex. 3.14) 10 Test of sentence structure hypotheses (POSITION contrasts)

                       General Linear Models Procedure
                      Multivariate Analysis of Variance

                  M Matrix Describing Transformed Variables
                   P1            P2            P3            P4            P5

SUBPRED             1             1            -1            -1             0
ADJNOUN             1            -1             1            -1             0
SPXAN               1            -1            -1             1             0
RELPN               1             1             1             1            -4


                            E = Error SS&CP Matrix
                  SUBPRED          ADJNOUN            SPXAN            RELPN

 SUBPRED     694.18181818     54.909090909     23.818181818     562.72727273
 ADJNOUN     54.909090909     1370.5454545     -48.90909091     53.636363636
 SPXAN       23.818181818     -48.90909091     482.18181818     863.27272727
 RELPN       562.72727273     53.636363636     863.27272727     6026.9090909

Profile Analysis Example: PROBE1 (Timm, Ex. 3.14) 11 Test of sentence structure hypotheses (POSITION contrasts)

                       General Linear Models Procedure
                      Multivariate Analysis of Variance

         Partial Correlation Coefficients from the Error SS&CP Matrix
    of the Variables Defined by the Specified Transformation / Prob > |r|
              DF = 10      SUBPRED   ADJNOUN     SPXAN     RELPN

              SUBPRED     1.000000  0.056294  0.041169  0.275115
                            0.0001    0.8694    0.9043    0.4129
              ADJNOUN     0.056294  1.000000 -0.060164  0.018662
                            0.8694    0.0001    0.8605    0.9566
              SPXAN       0.041169 -0.060164  1.000000  0.506402
                            0.9043    0.8605    0.0001    0.1119
              RELPN       0.275115  0.018662  0.506402  1.000000
                            0.4129    0.9566    0.1119    0.0001



Profile Analysis Example: PROBE1 (Timm, Ex. 3.14) 12 Test of sentence structure hypotheses (POSITION contrasts)

                       General Linear Models Procedure
                      Multivariate Analysis of Variance

          Characteristic Roots and Vectors of: E Inverse * H, where
       H = Type III SS&CP Matrix for INTERCEPT   E = Error SS&CP Matrix

               Variables have been transformed by the M Matrix

Characteristic   Percent                Characteristic Vector  V'EV=1
     Root
                                       SUBPRED        ADJNOUN          SPXAN
                                         RELPN
    3.02859542    100.00            0.00094372     0.02510304     0.02385523
                                   -0.00369971

    0.00000000      0.00            0.03794328    -0.00049531    -0.00047069
                                    0.00007300

    0.00000000      0.00           -0.01194271     0.00494892    -0.02255171
                                    0.01520419

    0.00000000      0.00           -0.00072946    -0.00901187     0.04203549
                                    0.00000000



               Manova Test Criteria and Exact F Statistics for
                the Hypothesis of no Overall INTERCEPT Effect
           on the variables defined by the M Matrix Transformation
       H = Type III SS&CP Matrix for INTERCEPT   E = Error SS&CP Matrix

                             S=1    M=1    N=2.5

 Statistic                     Value          F      Num DF    Den DF  Pr > F
 Wilks' Lambda              0.24822547     5.3000         4         7  0.0277
 Pillai's Trace             0.75177453     5.3000         4         7  0.0277
 Hotelling-Lawley Trace     3.02859542     5.3000         4         7  0.0277
 Roy's Greatest Root        3.02859542     5.3000         4         7  0.0277

Profile Analysis Example: PROBE1 (Timm, Ex. 3.14) 13 Test of sentence structure hypotheses (POSITION contrasts)

                       General Linear Models Procedure
                      Multivariate Analysis of Variance

Dependent Variable: SUBPRED

Source                  DF     Type III SS    Mean Square   F Value     Pr > F
INTERCEPT                1      0.81818182     0.81818182      0.01     0.9157

Error                   10    694.18181818    69.41818182

Dependent Variable: ADJNOUN

Source                  DF     Type III SS    Mean Square   F Value     Pr > F
INTERCEPT                1    3316.4545455   3316.4545455     24.20     0.0006

Error                   10    1370.5454545    137.0545455

Dependent Variable: SPXAN

Source                  DF     Type III SS    Mean Square   F Value     Pr > F
INTERCEPT                1    152.81818182   152.81818182      3.17     0.1054

Error                   10    482.18181818    48.21818182

Dependent Variable: RELPN

Source                  DF     Type III SS    Mean Square   F Value     Pr > F
INTERCEPT                1      0.09090909     0.09090909      0.00     0.9904

Error                   10   6026.90909091   602.69090909