IBM SPSS Web Report - Output9

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Separator Separator
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Log
GLM VAR00001 VAR00002 VAR00003 VAR00004 VAR00005 VAR00006 VAR00007 VAR00008 VAR00009 VAR00010 VAR00011 VAR00012 VAR00013 VAR00014 VAR00015 VAR00016 VAR00017 VAR00018 VAR00019 VAR00020 VAR00021 VAR00022 VAR00023 VAR00024 VAR00025 VAR00026 VAR00027 VAR00028 VAR00029 VAR00030 VAR00031 VAR00032 VAR00033 VAR00034 VAR00035 VAR00036 VAR00037 VAR00038 VAR00039 VAR00040 VAR00041 VAR00042 VAR00043 VAR00044 VAR00045
  /WSFACTOR=method 3 Polynomial speaker 5 Polynomial style 3 Polynomial
  /METHOD=SSTYPE(3)
  /PLOT=PROFILE(method speaker style method*speaker method*style method*speaker*style)
  /EMMEANS=TABLES(OVERALL)
  /EMMEANS=TABLES(method) COMPARE ADJ(LSD)
  /EMMEANS=TABLES(speaker) COMPARE ADJ(LSD)
  /EMMEANS=TABLES(style) COMPARE ADJ(LSD)
  /EMMEANS=TABLES(method*speaker)
  /EMMEANS=TABLES(method*style)
  /EMMEANS=TABLES(speaker*style)
  /EMMEANS=TABLES(method*speaker*style)
  /PRINT=DESCRIPTIVE ETASQ
  /CRITERIA=ALPHA(.05)
  /WSDESIGN=method speaker style method*speaker method*style speaker*style method*speaker*style.
General Linear Model

[DataSet5] /Volumes/T405/T40521/work/ljuvela/Zerophase_listening_test/LISTENING_TEST_T2/RMANOVA.sav
General Linear Model
Within-Subjects FactorsWithin-Subjects Factors, table, Measure, MEASURE_1, 1 layers, 1 levels of column headers and 3 levels of row headers, table with 4 columns and 48 rows
MEASURE_1 MEASURE_1
method speaker style Dependent Variable
1 1 1 VAR00001
2 VAR00002
3 VAR00003
2 1 VAR00004
2 VAR00005
3 VAR00006
3 1 VAR00007
2 VAR00008
3 VAR00009
4 1 VAR00010
2 VAR00011
3 VAR00012
5 1 VAR00013
2 VAR00014
3 VAR00015
2 1 1 VAR00016
2 VAR00017
3 VAR00018
2 1 VAR00019
2 VAR00020
3 VAR00021
3 1 VAR00022
2 VAR00023
3 VAR00024
4 1 VAR00025
2 VAR00026
3 VAR00027
5 1 VAR00028
2 VAR00029
3 VAR00030
3 1 1 VAR00031
2 VAR00032
3 VAR00033
2 1 VAR00034
2 VAR00035
3 VAR00036
3 1 VAR00037
2 VAR00038
3 VAR00039
4 1 VAR00040
2 VAR00041
3 VAR00042
5 1 VAR00043
2 VAR00044
3 VAR00045
General Linear Model
Descriptive StatisticsDescriptive Statistics, table, 1 levels of column headers and 1 levels of row headers, table with 4 columns and 47 rows
  Mean Std. Deviation N
VAR00001 51.5867 17.60495 15
VAR00002 59.0400 15.74333 15
VAR00003 46.6400 16.53571 15
VAR00004 58.8533 20.89859 15
VAR00005 56.0533 16.25818 15
VAR00006 42.5867 16.31607 15
VAR00007 54.6000 17.81123 15
VAR00008 45.7467 18.86894 15
VAR00009 46.0400 17.30833 15
VAR00010 49.1467 15.80768 15
VAR00011 50.1600 16.77263 15
VAR00012 30.6933 13.57369 15
VAR00013 61.5067 17.68597 15
VAR00014 41.5333 17.72354 15
VAR00015 43.0533 16.70354 15
VAR00016 47.1200 14.88351 15
VAR00017 55.0800 15.60308 15
VAR00018 43.7333 18.37571 15
VAR00019 48.8400 15.60077 15
VAR00020 51.6267 17.84503 15
VAR00021 32.3333 19.60724 15
VAR00022 47.3867 19.73474 15
VAR00023 35.9333 19.02835 15
VAR00024 35.6133 20.80405 15
VAR00025 44.9333 14.87772 15
VAR00026 41.3333 16.92398 15
VAR00027 19.3600 14.40083 15
VAR00028 61.0133 16.65712 15
VAR00029 34.0400 19.55800 15
VAR00030 24.3600 16.21484 15
VAR00031 37.5867 18.04320 15
VAR00032 30.0000 16.75709 15
VAR00033 20.9467 14.72674 15
VAR00034 32.8933 19.95579 15
VAR00035 25.8000 16.88584 15
VAR00036 39.1733 13.68876 15
VAR00037 40.2133 19.00789 15
VAR00038 35.1733 17.34274 15
VAR00039 49.7333 18.13736 15
VAR00040 35.2800 12.66013 15
VAR00041 41.5867 18.99014 15
VAR00042 28.4133 12.44105 15
VAR00043 51.8933 18.53134 15
VAR00044 42.6267 14.07711 15
VAR00045 38.0933 19.04549 15
General Linear Model
Multivariate TestsaMultivariate Tests, table, 1 levels of column headers and 2 levels of row headers, table with 8 columns and 33 rows
Effect Value F Hypothesis df Error df Sig. Partial Eta Squared
method Pillai's Trace .891 53.140b 2.000 13.000 .000 .891
Wilks' Lambda .109 53.140b 2.000 13.000 .000 .891
Hotelling's Trace 8.175 53.140b 2.000 13.000 .000 .891
Roy's Largest Root 8.175 53.140b 2.000 13.000 .000 .891
speaker Pillai's Trace .684 5.944b 4.000 11.000 .008 .684
Wilks' Lambda .316 5.944b 4.000 11.000 .008 .684
Hotelling's Trace 2.161 5.944b 4.000 11.000 .008 .684
Roy's Largest Root 2.161 5.944b 4.000 11.000 .008 .684
style Pillai's Trace .718 16.577b 2.000 13.000 .000 .718
Wilks' Lambda .282 16.577b 2.000 13.000 .000 .718
Hotelling's Trace 2.550 16.577b 2.000 13.000 .000 .718
Roy's Largest Root 2.550 16.577b 2.000 13.000 .000 .718
method * speaker Pillai's Trace .916 9.504b 8.000 7.000 .004 .916
Wilks' Lambda .084 9.504b 8.000 7.000 .004 .916
Hotelling's Trace 10.861 9.504b 8.000 7.000 .004 .916
Roy's Largest Root 10.861 9.504b 8.000 7.000 .004 .916
method * style Pillai's Trace .745 8.044b 4.000 11.000 .003 .745
Wilks' Lambda .255 8.044b 4.000 11.000 .003 .745
Hotelling's Trace 2.925 8.044b 4.000 11.000 .003 .745
Roy's Largest Root 2.925 8.044b 4.000 11.000 .003 .745
speaker * style Pillai's Trace .899 7.790b 8.000 7.000 .007 .899
Wilks' Lambda .101 7.790b 8.000 7.000 .007 .899
Hotelling's Trace 8.903 7.790b 8.000 7.000 .007 .899
Roy's Largest Root 8.903 7.790b 8.000 7.000 .007 .899
method * speaker * style Pillai's Trace .c . . . . .
Wilks' Lambda .c . . . . .
Hotelling's Trace .c . . . . .
Roy's Largest Root .c . . . . .
a. Design: Intercept
Within Subjects Design: method + speaker + style + method * speaker + method * style + speaker * style + method * speaker * style
b. Exact statistic
c. Cannot produce multivariate test statistics because of insufficient residual degrees of freedom.
General Linear Model
Mauchly's Test of SphericityaMauchly's Test of Sphericity, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 1 levels of row headers, table with 8 columns and 14 rows
MEASURE_1 MEASURE_1
Within Subjects Effect Mauchly's W Approx. Chi-Square df Sig. Epsilonb
Greenhouse-Geisser Huynh-Feldt Lower-bound
method .524 8.409 2 .015 .677 .724 .500
speaker .630 5.734 9 .768 .832 1.000 .250
style .669 5.229 2 .073 .751 .822 .500
method * speaker .014 47.267 35 .104 .523 .774 .125
method * style .058 35.456 9 .000 .499 .582 .250
speaker * style .024 41.510 35 .249 .543 .818 .125
method * speaker * style .000 . 135 . .371 .676 .063
Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix.
a. Design: Intercept
Within Subjects Design: method + speaker + style + method * speaker + method * style + speaker * style + method * speaker * style
b. May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in the Tests of Within-Subjects Effects table.
General Linear Model
Tests of Within-Subjects EffectsTests of Within-Subjects Effects, table, Measure, MEASURE_1, 1 layers, 1 levels of column headers and 2 levels of row headers, table with 8 columns and 59 rows
MEASURE_1 MEASURE_1
Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared
method Sphericity Assumed 17922.885 2 8961.442 28.992 .000 .674
Greenhouse-Geisser 17922.885 1.355 13229.653 28.992 .000 .674
Huynh-Feldt 17922.885 1.449 12370.290 28.992 .000 .674
Lower-bound 17922.885 1.000 17922.885 28.992 .000 .674
Error(method) Sphericity Assumed 8654.712 28 309.097      
Greenhouse-Geisser 8654.712 18.967 456.315      
Huynh-Feldt 8654.712 20.284 426.674      
Lower-bound 8654.712 14.000 618.194      
speaker Sphericity Assumed 3587.253 4 896.813 6.525 .000 .318
Greenhouse-Geisser 3587.253 3.327 1078.257 6.525 .001 .318
Huynh-Feldt 3587.253 4.000 896.813 6.525 .000 .318
Lower-bound 3587.253 1.000 3587.253 6.525 .023 .318
Error(speaker) Sphericity Assumed 7696.339 56 137.435      
Greenhouse-Geisser 7696.339 46.577 165.240      
Huynh-Feldt 7696.339 56.000 137.435      
Lower-bound 7696.339 14.000 549.738      
style Sphericity Assumed 16705.741 2 8352.870 27.930 .000 .666
Greenhouse-Geisser 16705.741 1.502 11119.221 27.930 .000 .666
Huynh-Feldt 16705.741 1.643 10166.453 27.930 .000 .666
Lower-bound 16705.741 1.000 16705.741 27.930 .000 .666
Error(style) Sphericity Assumed 8373.946 28 299.070      
Greenhouse-Geisser 8373.946 21.034 398.117      
Huynh-Feldt 8373.946 23.005 364.004      
Lower-bound 8373.946 14.000 598.139      
method * speaker Sphericity Assumed 10494.075 8 1311.759 26.655 .000 .656
Greenhouse-Geisser 10494.075 4.185 2507.405 26.655 .000 .656
Huynh-Feldt 10494.075 6.193 1694.627 26.655 .000 .656
Lower-bound 10494.075 1.000 10494.075 26.655 .000 .656
Error(method*speaker) Sphericity Assumed 5511.769 112 49.212      
Greenhouse-Geisser 5511.769 58.593 94.068      
Huynh-Feldt 5511.769 86.696 63.576      
Lower-bound 5511.769 14.000 393.698      
method * style Sphericity Assumed 4863.979 4 1215.995 16.786 .000 .545
Greenhouse-Geisser 4863.979 1.996 2436.378 16.786 .000 .545
Huynh-Feldt 4863.979 2.328 2089.220 16.786 .000 .545
Lower-bound 4863.979 1.000 4863.979 16.786 .001 .545
Error(method*style) Sphericity Assumed 4056.798 56 72.443      
Greenhouse-Geisser 4056.798 27.950 145.147      
Huynh-Feldt 4056.798 32.594 124.465      
Lower-bound 4056.798 14.000 289.771      
speaker * style Sphericity Assumed 12486.563 8 1560.820 12.894 .000 .479
Greenhouse-Geisser 12486.563 4.346 2873.388 12.894 .000 .479
Huynh-Feldt 12486.563 6.545 1907.931 12.894 .000 .479
Lower-bound 12486.563 1.000 12486.563 12.894 .003 .479
Error(speaker*style) Sphericity Assumed 13557.457 112 121.049      
Greenhouse-Geisser 13557.457 60.838 222.844      
Huynh-Feldt 13557.457 91.624 147.969      
Lower-bound 13557.457 14.000 968.390      
method * speaker * style Sphericity Assumed 7505.731 16 469.108 11.443 .000 .450
Greenhouse-Geisser 7505.731 5.941 1263.329 11.443 .000 .450
Huynh-Feldt 7505.731 10.810 694.307 11.443 .000 .450
Lower-bound 7505.731 1.000 7505.731 11.443 .004 .450
Error(method*speaker*style) Sphericity Assumed 9182.558 224 40.994      
Greenhouse-Geisser 9182.558 83.177 110.397      
Huynh-Feldt 9182.558 151.346 60.673      
Lower-bound 9182.558 14.000 655.897      
General Linear Model
Tests of Within-Subjects ContrastsTests of Within-Subjects Contrasts, table, Measure, MEASURE_1, 1 layers, 1 levels of column headers and 4 levels of row headers, table with 10 columns and 91 rows
MEASURE_1 MEASURE_1
Source method speaker style Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared
method Linear     17639.428 1 17639.428 50.089 .000 .782
Quadratic     283.456 1 283.456 1.065 .319 .071
Error(method) Linear     4930.224 14 352.159      
Quadratic     3724.488 14 266.035      
speaker   Linear   198.145 1 198.145 1.332 .268 .087
Quadratic   579.340 1 579.340 3.292 .091 .190
Cubic   1696.577 1 1696.577 20.182 .001 .590
Order 4   1113.190 1 1113.190 7.899 .014 .361
Error(speaker)   Linear   2082.832 14 148.774      
Quadratic   2463.613 14 175.972      
Cubic   1176.910 14 84.065      
Order 4   1972.984 14 140.927      
style     Linear 16576.563 1 16576.563 35.681 .000 .718
Quadratic 129.178 1 129.178 .967 .342 .065
Error(style)     Linear 6504.066 14 464.576      
Quadratic 1869.880 14 133.563      
method * speaker Linear Linear   5286.259 1 5286.259 51.927 .000 .788
Quadratic   251.741 1 251.741 12.766 .003 .477
Cubic   52.998 1 52.998 .856 .371 .058
Order 4   581.248 1 581.248 14.068 .002 .501
Quadratic Linear   3541.829 1 3541.829 59.716 .000 .810
Quadratic   519.704 1 519.704 9.642 .008 .408
Cubic   25.269 1 25.269 .944 .348 .063
Order 4   235.025 1 235.025 8.117 .013 .367
Error(method*speaker) Linear Linear   1425.237 14 101.803      
Quadratic   276.081 14 19.720      
Cubic   866.832 14 61.917      
Order 4   578.437 14 41.317      
Quadratic Linear   830.357 14 59.311      
Quadratic   754.585 14 53.899      
Cubic   374.854 14 26.775      
Order 4   405.386 14 28.956      
method * style Linear   Linear 1530.473 1 1530.473 9.798 .007 .412
Quadratic 488.705 1 488.705 22.280 .000 .614
Quadratic   Linear 2480.040 1 2480.040 25.460 .000 .645
Quadratic 364.762 1 364.762 25.634 .000 .647
Error(method*style) Linear   Linear 2186.763 14 156.197      
Quadratic 307.091 14 21.935      
Quadratic   Linear 1363.727 14 97.409      
Quadratic 199.216 14 14.230      
speaker * style   Linear Linear 3150.951 1 3150.951 22.762 .000 .619
Quadratic 1245.218 1 1245.218 11.324 .005 .447
Quadratic Linear 1406.423 1 1406.423 6.961 .019 .332
Quadratic .672 1 .672 .015 .905 .001
Cubic Linear 5.921 1 5.921 .063 .806 .004
Quadratic 2588.770 1 2588.770 23.866 .000 .630
Order 4 Linear 812.022 1 812.022 11.524 .004 .451
Quadratic 3276.585 1 3276.585 16.470 .001 .541
Error(speaker*style)   Linear Linear 1937.982 14 138.427      
Quadratic 1539.528 14 109.966      
Quadratic Linear 2828.742 14 202.053      
Quadratic 635.362 14 45.383      
Cubic Linear 1325.476 14 94.677      
Quadratic 1518.577 14 108.470      
Order 4 Linear 986.520 14 70.466      
Quadratic 2785.271 14 198.948      
method * speaker * style Linear Linear Linear 177.127 1 177.127 3.023 .104 .178
Quadratic 1260.689 1 1260.689 16.976 .001 .548
Quadratic Linear 1906.837 1 1906.837 140.014 .000 .909
Quadratic 221.314 1 221.314 22.345 .000 .615
Cubic Linear 549.127 1 549.127 7.428 .016 .347
Quadratic 78.877 1 78.877 4.197 .060 .231
Order 4 Linear 65.975 1 65.975 1.598 .227 .102
Quadratic 73.570 1 73.570 .857 .370 .058
Quadratic Linear Linear 1639.736 1 1639.736 41.665 .000 .748
Quadratic 490.330 1 490.330 14.769 .002 .513
Quadratic Linear 183.924 1 183.924 7.593 .015 .352
Quadratic 62.539 1 62.539 1.840 .196 .116
Cubic Linear 315.842 1 315.842 8.240 .012 .370
Quadratic 327.771 1 327.771 5.867 .030 .295
Order 4 Linear 8.748 1 8.748 .340 .569 .024
Quadratic 143.326 1 143.326 4.947 .043 .261
Error(method*speaker*style) Linear Linear Linear 820.351 14 58.597      
Quadratic 1039.701 14 74.264      
Quadratic Linear 190.664 14 13.619      
Quadratic 138.662 14 9.904      
Cubic Linear 1034.915 14 73.923      
Quadratic 263.107 14 18.793      
Order 4 Linear 577.987 14 41.285      
Quadratic 1202.318 14 85.880      
Quadratic Linear Linear 550.973 14 39.355      
Quadratic 464.804 14 33.200      
Quadratic Linear 339.117 14 24.223      
Quadratic 475.833 14 33.988      
Cubic Linear 536.649 14 38.332      
Quadratic 782.100 14 55.864      
Order 4 Linear 359.797 14 25.700      
Quadratic 405.580 14 28.970      
General Linear Model
Tests of Between-Subjects EffectsTests of Between-Subjects Effects, table, Measure, MEASURE_1, Transformed Variable, Average, 1 layers, 1 levels of column headers and 1 levels of row headers, table with 7 columns and 6 rows
MEASURE_1 MEASURE_1
Average Average
Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared
Intercept 1215218.537 1 1215218.537 132.735 .000 .905
Error 128173.179 14 9155.227      
Estimated Marginal Means
1. Grand Mean1. Grand Mean, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 0 levels of row headers, table with 4 columns and 5 rows
MEASURE_1 MEASURE_1
Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
42.430 3.683 34.531 50.329
2. method
EstimatesEstimates, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 1 levels of row headers, table with 5 columns and 7 rows
MEASURE_1 MEASURE_1
method Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 49.149 3.692 41.232 57.067
2 41.514 3.950 33.041 49.987
3 36.628 3.769 28.544 44.711
2. method
Pairwise ComparisonsPairwise Comparisons, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 2 levels of row headers, table with 7 columns and 13 rows
MEASURE_1 MEASURE_1
(I) method (J) method Mean Difference (I-J) Std. Error Sig.b 95% Confidence Interval for Differenceb
Lower Bound Upper Bound
1 2 7.636* .974 .000 5.547 9.724
3 12.522* 1.769 .000 8.727 16.316
2 1 -7.636* .974 .000 -9.724 -5.547
3 4.886* 2.041 .031 .509 9.263
3 1 -12.522* 1.769 .000 -16.316 -8.727
2 -4.886* 2.041 .031 -9.263 -.509
Based on estimated marginal means
*. The mean difference is significant at the
b. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).
2. method
Multivariate TestsMultivariate Tests, table, 1 levels of column headers and 1 levels of row headers, table with 7 columns and 8 rows
  Value F Hypothesis df Error df Sig. Partial Eta Squared
Pillai's trace .891 53.140a 2.000 13.000 .000 .891
Wilks' lambda .109 53.140a 2.000 13.000 .000 .891
Hotelling's trace 8.175 53.140a 2.000 13.000 .000 .891
Roy's largest root 8.175 53.140a 2.000 13.000 .000 .891
Each F tests the multivariate effect of method. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.
a. Exact statistic
3. speaker
EstimatesEstimates, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 1 levels of row headers, table with 5 columns and 9 rows
MEASURE_1 MEASURE_1
speaker Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 43.526 3.490 36.041 51.011
2 43.129 3.817 34.942 51.316
3 43.382 4.245 34.278 52.487
4 37.879 3.303 30.795 44.962
5 44.236 4.026 35.600 52.871
3. speaker
Pairwise ComparisonsPairwise Comparisons, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 2 levels of row headers, table with 7 columns and 27 rows
MEASURE_1 MEASURE_1
(I) speaker (J) speaker Mean Difference (I-J) Std. Error Sig.b 95% Confidence Interval for Differenceb
Lower Bound Upper Bound
1 2 .397 .962 .686 -1.667 2.461
3 .144 1.663 .932 -3.423 3.710
4 5.647* 1.390 .001 2.666 8.629
5 -.710 1.365 .611 -3.638 2.219
2 1 -.397 .962 .686 -2.461 1.667
3 -.253 1.465 .865 -3.395 2.888
4 5.250* 1.259 .001 2.550 7.951
5 -1.107 1.333 .421 -3.967 1.753
3 1 -.144 1.663 .932 -3.710 3.423
2 .253 1.465 .865 -2.888 3.395
4 5.504* 1.561 .003 2.156 8.851
5 -.853 1.770 .637 -4.650 2.943
4 1 -5.647* 1.390 .001 -8.629 -2.666
2 -5.250* 1.259 .001 -7.951 -2.550
3 -5.504* 1.561 .003 -8.851 -2.156
5 -6.357* 1.340 .000 -9.230 -3.484
5 1 .710 1.365 .611 -2.219 3.638
2 1.107 1.333 .421 -1.753 3.967
3 .853 1.770 .637 -2.943 4.650
4 6.357* 1.340 .000 3.484 9.230
Based on estimated marginal means
*. The mean difference is significant at the
b. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).
3. speaker
Multivariate TestsMultivariate Tests, table, 1 levels of column headers and 1 levels of row headers, table with 7 columns and 8 rows
  Value F Hypothesis df Error df Sig. Partial Eta Squared
Pillai's trace .684 5.944a 4.000 11.000 .008 .684
Wilks' lambda .316 5.944a 4.000 11.000 .008 .684
Hotelling's trace 2.161 5.944a 4.000 11.000 .008 .684
Roy's largest root 2.161 5.944a 4.000 11.000 .008 .684
Each F tests the multivariate effect of speaker. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.
a. Exact statistic
4. style
EstimatesEstimates, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 1 levels of row headers, table with 5 columns and 7 rows
MEASURE_1 MEASURE_1
style Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 48.190 3.776 40.092 56.288
2 43.049 3.800 34.898 51.199
3 36.052 3.828 27.842 44.261
4. style
Pairwise ComparisonsPairwise Comparisons, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 2 levels of row headers, table with 7 columns and 13 rows
MEASURE_1 MEASURE_1
(I) style (J) style Mean Difference (I-J) Std. Error Sig.b 95% Confidence Interval for Differenceb
Lower Bound Upper Bound
1 2 5.141* 1.249 .001 2.463 7.820
3 12.139* 2.032 .000 7.780 16.497
2 1 -5.141* 1.249 .001 -7.820 -2.463
3 6.997* 1.512 .000 3.754 10.240
3 1 -12.139* 2.032 .000 -16.497 -7.780
2 -6.997* 1.512 .000 -10.240 -3.754
Based on estimated marginal means
*. The mean difference is significant at the
b. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).
4. style
Multivariate TestsMultivariate Tests, table, 1 levels of column headers and 1 levels of row headers, table with 7 columns and 8 rows
  Value F Hypothesis df Error df Sig. Partial Eta Squared
Pillai's trace .718 16.577a 2.000 13.000 .000 .718
Wilks' lambda .282 16.577a 2.000 13.000 .000 .718
Hotelling's trace 2.550 16.577a 2.000 13.000 .000 .718
Roy's largest root 2.550 16.577a 2.000 13.000 .000 .718
Each F tests the multivariate effect of style. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.
a. Exact statistic
Estimated Marginal Means
5. method * speaker5. method * speaker, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 2 levels of row headers, table with 6 columns and 19 rows
MEASURE_1 MEASURE_1
method speaker Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 1 52.422 3.647 44.600 60.244
2 52.498 4.007 43.903 61.093
3 48.796 4.078 40.049 57.542
4 43.333 3.569 35.679 50.987
5 48.698 4.064 39.981 57.415
2 1 48.644 3.903 40.273 57.016
2 44.267 4.086 35.504 53.029
3 39.644 4.709 29.546 49.743
4 35.209 3.672 27.332 43.085
5 39.804 4.114 30.980 48.629
3 1 29.511 3.946 21.048 37.974
2 32.622 3.986 24.074 41.171
3 41.707 4.405 32.258 51.155
4 35.093 3.207 28.215 41.971
5 44.204 4.153 35.296 53.113
Estimated Marginal Means
6. method * style6. method * style, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 2 levels of row headers, table with 6 columns and 13 rows
MEASURE_1 MEASURE_1
method style Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 1 55.139 4.111 46.321 63.956
2 50.507 3.820 42.313 58.700
3 41.803 3.827 33.594 50.011
2 1 49.859 3.913 41.466 58.252
2 43.603 4.127 34.751 52.454
3 31.080 4.236 21.994 40.166
3 1 39.573 4.091 30.800 48.347
2 35.037 3.965 26.534 43.541
3 35.272 3.642 27.460 43.084
Estimated Marginal Means
7. speaker * style7. speaker * style, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 2 levels of row headers, table with 6 columns and 19 rows
MEASURE_1 MEASURE_1
speaker style Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 1 45.431 3.671 37.557 53.305
2 48.040 3.631 40.253 55.827
3 37.107 3.974 28.583 45.631
2 1 46.862 4.278 37.686 56.039
2 44.493 3.956 36.009 52.978
3 38.031 4.075 29.292 46.770
3 1 47.400 4.354 38.062 56.738
2 38.951 4.454 29.399 48.503
3 43.796 4.693 33.731 53.861
4 1 43.120 3.524 35.561 50.679
2 44.360 4.139 35.482 53.238
3 26.156 3.279 19.123 33.188
5 1 58.138 4.367 48.772 67.503
2 39.400 4.260 30.263 48.537
3 35.169 4.373 25.789 44.549
Estimated Marginal Means
8. method * speaker * style8. method * speaker * style, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 3 levels of row headers, table with 7 columns and 49 rows
MEASURE_1 MEASURE_1
method speaker style Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 1 1 51.587 4.546 41.837 61.336
2 59.040 4.065 50.322 67.758
3 46.640 4.270 37.483 55.797
2 1 58.853 5.396 47.280 70.427
2 56.053 4.198 47.050 65.057
3 42.587 4.213 33.551 51.622
3 1 54.600 4.599 44.736 64.464
2 45.747 4.872 35.297 56.196
3 46.040 4.469 36.455 55.625
4 1 49.147 4.082 40.393 57.901
2 50.160 4.331 40.872 59.448
3 30.693 3.505 23.176 38.210
5 1 61.507 4.566 51.713 71.301
2 41.533 4.576 31.718 51.348
3 43.053 4.313 33.803 52.303
2 1 1 47.120 3.843 38.878 55.362
2 55.080 4.029 46.439 63.721
3 43.733 4.745 33.557 53.909
2 1 48.840 4.028 40.201 57.479
2 51.627 4.608 41.744 61.509
3 32.333 5.063 21.475 43.191
3 1 47.387 5.095 36.458 58.315
2 35.933 4.913 25.396 46.471
3 35.613 5.372 24.092 47.134
4 1 44.933 3.841 36.694 53.172
2 41.333 4.370 31.961 50.706
3 19.360 3.718 11.385 27.335
5 1 61.013 4.301 51.789 70.238
2 34.040 5.050 23.209 44.871
3 24.360 4.187 15.381 33.339
3 1 1 37.587 4.659 27.595 47.579
2 30.000 4.327 20.720 39.280
3 20.947 3.802 12.791 29.102
2 1 32.893 5.153 21.842 43.944
2 25.800 4.360 16.449 35.151
3 39.173 3.534 31.593 46.754
3 1 40.213 4.908 29.687 50.740
2 35.173 4.478 25.569 44.777
3 49.733 4.683 39.689 59.777
4 1 35.280 3.269 28.269 42.291
2 41.587 4.903 31.070 52.103
3 28.413 3.212 21.524 35.303
5 1 51.893 4.785 41.631 62.156
2 42.627 3.635 34.831 50.422
3 38.093 4.918 27.546 48.640
Profile Plots
method: 3 Estimated Marginal Means: 36.628 method: 2 Estimated Marginal Means: 41.514 method: 1 Estimated Marginal Means: 49.149 method: 2 Estimated Marginal Means: 41.514 method: 1 Estimated Marginal Means: 49.149 37.50 40.00 42.50 45.00 47.50 50.00 50.00 47.50 45.00 42.50 40.00 37.50 1 2 3 3 2 1
Profile Plots
speaker: 5 Estimated Marginal Means: 44.236 speaker: 4 Estimated Marginal Means: 37.879 speaker: 3 Estimated Marginal Means: 43.382 speaker: 2 Estimated Marginal Means: 43.129 speaker: 1 Estimated Marginal Means: 43.526 speaker: 4 Estimated Marginal Means: 37.879 speaker: 3 Estimated Marginal Means: 43.382 speaker: 2 Estimated Marginal Means: 43.129 speaker: 1 Estimated Marginal Means: 43.526 38.00 40.00 42.00 44.00 44.00 42.00 40.00 38.00 1 2 3 4 5 5 4 3 2 1
Profile Plots
style: 3 Estimated Marginal Means: 36.052 style: 2 Estimated Marginal Means: 43.049 style: 1 Estimated Marginal Means: 48.19 style: 2 Estimated Marginal Means: 43.049 style: 1 Estimated Marginal Means: 48.19 37.50 40.00 42.50 45.00 47.50 50.00 50.00 47.50 45.00 42.50 40.00 37.50 1 2 3 3 2 1
Profile Plots
method: 3 Estimated Marginal Means: 44.204 speaker: 5 method: 2 Estimated Marginal Means: 39.804 speaker: 5 method: 1 Estimated Marginal Means: 48.698 speaker: 5 method: 3 Estimated Marginal Means: 35.093 speaker: 4 method: 2 Estimated Marginal Means: 35.209 speaker: 4 method: 1 Estimated Marginal Means: 43.333 speaker: 4 method: 3 Estimated Marginal Means: 41.707 speaker: 3 method: 2 Estimated Marginal Means: 39.644 speaker: 3 method: 1 Estimated Marginal Means: 48.796 speaker: 3 method: 3 Estimated Marginal Means: 32.622 speaker: 2 method: 2 Estimated Marginal Means: 44.267 speaker: 2 method: 1 Estimated Marginal Means: 52.498 speaker: 2 method: 3 Estimated Marginal Means: 29.511 speaker: 1 method: 2 Estimated Marginal Means: 48.644 speaker: 1 method: 1 Estimated Marginal Means: 52.422 speaker: 1 method: 2 Estimated Marginal Means: 39.804 speaker: 5 method: 1 Estimated Marginal Means: 48.698 speaker: 5 method: 2 Estimated Marginal Means: 35.209 speaker: 4 method: 1 Estimated Marginal Means: 43.333 speaker: 4 method: 2 Estimated Marginal Means: 39.644 speaker: 3 method: 1 Estimated Marginal Means: 48.796 speaker: 3 method: 2 Estimated Marginal Means: 44.267 speaker: 2 method: 1 Estimated Marginal Means: 52.498 speaker: 2 method: 2 Estimated Marginal Means: 48.644 speaker: 1 method: 1 Estimated Marginal Means: 52.422 speaker: 1 25.00 30.00 35.00 40.00 45.00 50.00 55.00 55.00 50.00 45.00 40.00 35.00 30.00 25.00 1 2 3 3 2 1
Profile Plots
method: 3 Estimated Marginal Means: 35.272 style: 3 method: 2 Estimated Marginal Means: 31.08 style: 3 method: 1 Estimated Marginal Means: 41.803 style: 3 method: 3 Estimated Marginal Means: 35.037 style: 2 method: 2 Estimated Marginal Means: 43.603 style: 2 method: 1 Estimated Marginal Means: 50.507 style: 2 method: 3 Estimated Marginal Means: 39.573 style: 1 method: 2 Estimated Marginal Means: 49.859 style: 1 method: 1 Estimated Marginal Means: 55.139 style: 1 method: 2 Estimated Marginal Means: 31.08 style: 3 method: 1 Estimated Marginal Means: 41.803 style: 3 method: 2 Estimated Marginal Means: 43.603 style: 2 method: 1 Estimated Marginal Means: 50.507 style: 2 method: 2 Estimated Marginal Means: 49.859 style: 1 method: 1 Estimated Marginal Means: 55.139 style: 1 30.00 35.00 40.00 45.00 50.00 55.00 60.00 60.00 55.00 50.00 45.00 40.00 35.00 30.00 1 2 3 3 2 1
method * speaker * style
method: 3 Estimated Marginal Means: 51.893 speaker: 5 method: 2 Estimated Marginal Means: 61.013 speaker: 5 method: 1 Estimated Marginal Means: 61.507 speaker: 5 method: 3 Estimated Marginal Means: 35.28 speaker: 4 method: 2 Estimated Marginal Means: 44.933 speaker: 4 method: 1 Estimated Marginal Means: 49.147 speaker: 4 method: 3 Estimated Marginal Means: 40.213 speaker: 3 method: 2 Estimated Marginal Means: 47.387 speaker: 3 method: 1 Estimated Marginal Means: 54.60 speaker: 3 method: 3 Estimated Marginal Means: 32.893 speaker: 2 method: 2 Estimated Marginal Means: 48.84 speaker: 2 method: 1 Estimated Marginal Means: 58.853 speaker: 2 method: 3 Estimated Marginal Means: 37.587 speaker: 1 method: 2 Estimated Marginal Means: 47.12 speaker: 1 method: 1 Estimated Marginal Means: 51.587 speaker: 1 method: 2 Estimated Marginal Means: 61.013 speaker: 5 method: 1 Estimated Marginal Means: 61.507 speaker: 5 method: 2 Estimated Marginal Means: 44.933 speaker: 4 method: 1 Estimated Marginal Means: 49.147 speaker: 4 method: 2 Estimated Marginal Means: 47.387 speaker: 3 method: 1 Estimated Marginal Means: 54.60 speaker: 3 method: 2 Estimated Marginal Means: 48.84 speaker: 2 method: 1 Estimated Marginal Means: 58.853 speaker: 2 method: 2 Estimated Marginal Means: 47.12 speaker: 1 method: 1 Estimated Marginal Means: 51.587 speaker: 1 30.00 40.00 50.00 60.00 70.00 70.00 60.00 50.00 40.00 30.00 1 2 3 3 2 1
method * speaker * style
method: 3 Estimated Marginal Means: 42.627 speaker: 5 method: 2 Estimated Marginal Means: 34.04 speaker: 5 method: 1 Estimated Marginal Means: 41.533 speaker: 5 method: 3 Estimated Marginal Means: 41.587 speaker: 4 method: 2 Estimated Marginal Means: 41.333 speaker: 4 method: 1 Estimated Marginal Means: 50.16 speaker: 4 method: 3 Estimated Marginal Means: 35.173 speaker: 3 method: 2 Estimated Marginal Means: 35.933 speaker: 3 method: 1 Estimated Marginal Means: 45.747 speaker: 3 method: 3 Estimated Marginal Means: 25.80 speaker: 2 method: 2 Estimated Marginal Means: 51.627 speaker: 2 method: 1 Estimated Marginal Means: 56.053 speaker: 2 method: 3 Estimated Marginal Means: 30.00 speaker: 1 method: 2 Estimated Marginal Means: 55.08 speaker: 1 method: 1 Estimated Marginal Means: 59.04 speaker: 1 method: 2 Estimated Marginal Means: 34.04 speaker: 5 method: 1 Estimated Marginal Means: 41.533 speaker: 5 method: 2 Estimated Marginal Means: 41.333 speaker: 4 method: 1 Estimated Marginal Means: 50.16 speaker: 4 method: 2 Estimated Marginal Means: 35.933 speaker: 3 method: 1 Estimated Marginal Means: 45.747 speaker: 3 method: 2 Estimated Marginal Means: 51.627 speaker: 2 method: 1 Estimated Marginal Means: 56.053 speaker: 2 method: 2 Estimated Marginal Means: 55.08 speaker: 1 method: 1 Estimated Marginal Means: 59.04 speaker: 1 20.00 30.00 40.00 50.00 60.00 60.00 50.00 40.00 30.00 20.00 1 2 3 3 2 1
method * speaker * style
method: 3 Estimated Marginal Means: 38.093 speaker: 5 method: 2 Estimated Marginal Means: 24.36 speaker: 5 method: 1 Estimated Marginal Means: 43.053 speaker: 5 method: 3 Estimated Marginal Means: 28.413 speaker: 4 method: 2 Estimated Marginal Means: 19.36 speaker: 4 method: 1 Estimated Marginal Means: 30.693 speaker: 4 method: 3 Estimated Marginal Means: 49.733 speaker: 3 method: 2 Estimated Marginal Means: 35.613 speaker: 3 method: 1 Estimated Marginal Means: 46.04 speaker: 3 method: 3 Estimated Marginal Means: 39.173 speaker: 2 method: 2 Estimated Marginal Means: 32.333 speaker: 2 method: 1 Estimated Marginal Means: 42.587 speaker: 2 method: 3 Estimated Marginal Means: 20.947 speaker: 1 method: 2 Estimated Marginal Means: 43.733 speaker: 1 method: 1 Estimated Marginal Means: 46.64 speaker: 1 method: 2 Estimated Marginal Means: 24.36 speaker: 5 method: 1 Estimated Marginal Means: 43.053 speaker: 5 method: 2 Estimated Marginal Means: 19.36 speaker: 4 method: 1 Estimated Marginal Means: 30.693 speaker: 4 method: 2 Estimated Marginal Means: 35.613 speaker: 3 method: 1 Estimated Marginal Means: 46.04 speaker: 3 method: 2 Estimated Marginal Means: 32.333 speaker: 2 method: 1 Estimated Marginal Means: 42.587 speaker: 2 method: 2 Estimated Marginal Means: 43.733 speaker: 1 method: 1 Estimated Marginal Means: 46.64 speaker: 1 10.00 20.00 30.00 40.00 50.00 50.00 40.00 30.00 20.00 10.00 1 2 3 3 2 1
IBM SPSS Web Report
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