IBM SPSS Web Report - poggendorf_wide.spv   

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Log
Log - Log - August 19, 2020

NEW FILE.
DATASET NAME DataSet1 WINDOW=FRONT.
GET DATA /TYPE=XLSX
  /FILE='D:\Statistics Tutor\MagicStat\datasets\factorial ANOVA\within-subjects factorial\Poggendorff_wide.xlsx'
  /SHEET=name 'Poggendorff Illusion data'
  /CELLRANGE=full
  /READNAMES=on
  /ASSUMEDSTRWIDTH=32767.
EXECUTE.
DATASET NAME DataSet2 WINDOW=FRONT.
DATASET ACTIVATE DataSet2.
GLM Long_Med Long_Narrow Long_Wide Short_Med Short_Narrow Short_Wide
  /WSFACTOR=length 2 Polynomial width 3 Polynomial
  /METHOD=SSTYPE(3)
  /EMMEANS=TABLES(length) COMPARE ADJ(LSD)
  /EMMEANS=TABLES(width) COMPARE ADJ(LSD)
  /EMMEANS=TABLES(length*width) COMPARE (length) ADJ(LSD)
  /EMMEANS=TABLES(length*width) COMPARE (width) ADJ(LSD)
  /EMMEANS=TABLES(length*width) COMPARE (length) ADJ(BONFERRONI)
  /EMMEANS=TABLES(length*width) COMPARE (width) ADJ(BONFERRONI)
  /EMMEANS=TABLES(length*width) COMPARE (length) ADJ(SIDAK)
  /EMMEANS=TABLES(length*width) COMPARE (width) ADJ(SIDAK)
  /PRINT=DESCRIPTIVE ETASQ OPOWER
  /CRITERIA=ALPHA(.05)
  /WSDESIGN=length width length*width.

General Linear Model
General Linear Model - Active Dataset - August 19, 2020


[DataSet2] 

General Linear Model
General Linear Model - Within-Subjects Factors - August 19, 2020
Within-Subjects FactorsWithin-Subjects Factors, table, Measure, MEASURE_1, 1 layers, 1 levels of column headers and 2 levels of row headers, table with 3 columns and 9 rows
MEASURE_1 MEASURE_1
length width Dependent Variable
1 1 Long_Med
2 Long_Narrow
3 Long_Wide
2 1 Short_Med
2 Short_Narrow
3 Short_Wide
General Linear Model
General Linear Model - Descriptive Statistics - August 19, 2020
Descriptive StatisticsDescriptive Statistics, table, 1 levels of column headers and 1 levels of row headers, table with 4 columns and 8 rows
  Mean Std. Deviation N
Long_Med -3.9674 16.35577 34
Long_Narrow -2.3291 8.61393 34
Long_Wide -6.1262 25.11453 34
Short_Med -4.5400 20.52461 34
Short_Narrow -2.4785 9.96103 34
Short_Wide -8.7421 30.94692 34
General Linear Model
General Linear Model - Multivariate Tests - August 19, 2020
Multivariate TestsaMultivariate Tests, table, 1 levels of column headers and 2 levels of row headers, table with 10 columns and 17 rows
Effect Value F Hypothesis df Error df Sig. Partial Eta Squared Noncent. Parameter Observed Powerc
length Pillai's Trace .041 1.418b 1.000 33.000 .242 .041 1.418 .212
Wilks' Lambda .959 1.418b 1.000 33.000 .242 .041 1.418 .212
Hotelling's Trace .043 1.418b 1.000 33.000 .242 .041 1.418 .212
Roy's Largest Root .043 1.418b 1.000 33.000 .242 .041 1.418 .212
width Pillai's Trace .092 1.623b 2.000 32.000 .213 .092 3.246 .317
Wilks' Lambda .908 1.623b 2.000 32.000 .213 .092 3.246 .317
Hotelling's Trace .101 1.623b 2.000 32.000 .213 .092 3.246 .317
Roy's Largest Root .101 1.623b 2.000 32.000 .213 .092 3.246 .317
length * width Pillai's Trace .124 2.255b 2.000 32.000 .121 .124 4.510 .425
Wilks' Lambda .876 2.255b 2.000 32.000 .121 .124 4.510 .425
Hotelling's Trace .141 2.255b 2.000 32.000 .121 .124 4.510 .425
Roy's Largest Root .141 2.255b 2.000 32.000 .121 .124 4.510 .425
a. Design: Intercept
Within Subjects Design: length + width + length * width		  
b. Exact statistic  
c. Computed using alpha = .05  
General Linear Model
General Linear Model - Mauchly's Test of Sphericity - August 19, 2020
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 10 rows
MEASURE_1 MEASURE_1
Within Subjects Effect Mauchly's W Approx. Chi-Square df Sig. Epsilonb
Greenhouse-Geisser Huynh-Feldt Lower-bound
length 1.000 .000 0 . 1.000 1.000 1.000
width .131 65.012 2 .000 .535 .538 .500
length * width .881 4.072 2 .131 .893 .941 .500
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: length + width + length * width
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
General Linear Model - Tests of Within-Subjects Effects - August 19, 2020
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 10 columns and 28 rows
MEASURE_1 MEASURE_1
Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Noncent. Parameter Observed Powera
length Sphericity Assumed 63.137 1 63.137 1.418 .242 .041 1.418 .212
Greenhouse-Geisser 63.137 1.000 63.137 1.418 .242 .041 1.418 .212
Huynh-Feldt 63.137 1.000 63.137 1.418 .242 .041 1.418 .212
Lower-bound 63.137 1.000 63.137 1.418 .242 .041 1.418 .212
Error(length) Sphericity Assumed 1469.631 33 44.534          
Greenhouse-Geisser 1469.631 33.000 44.534          
Huynh-Feldt 1469.631 33.000 44.534          
Lower-bound 1469.631 33.000 44.534          
width Sphericity Assumed 880.396 2 440.198 2.292 .109 .065 4.584 .450
Greenhouse-Geisser 880.396 1.070 822.676 2.292 .138 .065 2.453 .323
Huynh-Feldt 880.396 1.077 817.522 2.292 .137 .065 2.468 .324
Lower-bound 880.396 1.000 880.396 2.292 .140 .065 2.292 .312
Error(width) Sphericity Assumed 12676.674 66 192.071          
Greenhouse-Geisser 12676.674 35.315 358.957          
Huynh-Feldt 12676.674 35.538 356.708          
Lower-bound 12676.674 33.000 384.142          
length * width Sphericity Assumed 59.145 2 29.573 3.129 .050 .087 6.257 .582
Greenhouse-Geisser 59.145 1.787 33.106 3.129 .057 .087 5.589 .549
Huynh-Feldt 59.145 1.882 31.428 3.129 .054 .087 5.888 .564
Lower-bound 59.145 1.000 59.145 3.129 .086 .087 3.129 .404
Error(length*width) Sphericity Assumed 623.840 66 9.452          
Greenhouse-Geisser 623.840 58.955 10.582          
Huynh-Feldt 623.840 62.104 10.045          
Lower-bound 623.840 33.000 18.904          
a. Computed using alpha = .05  
General Linear Model
General Linear Model - Tests of Within-Subjects Contrasts - August 19, 2020
Tests of Within-Subjects ContrastsTests of Within-Subjects Contrasts, table, Measure, MEASURE_1, 1 layers, 1 levels of column headers and 3 levels of row headers, table with 11 columns and 14 rows
MEASURE_1 MEASURE_1
Source length width Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Noncent. Parameter Observed Powera
length Linear   63.137 1 63.137 1.418 .242 .041 1.418 .212
Error(length) Linear   1469.631 33 44.534          
width   Linear 343.917 1 343.917 3.080 .089 .085 3.080 .399
Quadratic 536.479 1 536.479 1.969 .170 .056 1.969 .276
Error(width)   Linear 3685.054 33 111.668          
Quadratic 8991.621 33 272.473          
length * width Linear Linear 35.486 1 35.486 3.538 .069 .097 3.538 .447
Quadratic 23.659 1 23.659 2.666 .112 .075 2.666 .354
Error(length*width) Linear Linear 330.994 33 10.030          
Quadratic 292.846 33 8.874          
a. Computed using alpha = .05    
General Linear Model
General Linear Model - Tests of Between-Subjects Effects - August 19, 2020
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 9 columns and 7 rows
MEASURE_1 MEASURE_1
Average Average
Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Noncent. Parameter Observed Powera
Intercept 4501.004 1 4501.004 2.247 .143 .064 2.247 .307
Error 66101.106 33 2003.064          
a. Computed using alpha = .05
1. length
1. length - Estimates - August 19, 2020
EstimatesEstimates, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 1 levels of row headers, table with 5 columns and 6 rows
MEASURE_1 MEASURE_1
length Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 -4.141 2.816 -9.870 1.588
2 -5.254 3.485 -12.344 1.837
1. length
1. length - Pairwise Comparisons - August 19, 2020
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 8 rows
MEASURE_1 MEASURE_1
(I) length (J) length Mean Difference (I-J) Std. Error Sig.a 95% Confidence Interval for Differencea
Lower Bound Upper Bound
1 2 1.113 .934 .242 -.789 3.014
2 1 -1.113 .934 .242 -3.014 .789
Based on estimated marginal means
a. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).
1. length
1. length - Multivariate Tests - August 19, 2020
Multivariate TestsMultivariate Tests, table, 1 levels of column headers and 1 levels of row headers, table with 9 columns and 9 rows
  Value F Hypothesis df Error df Sig. Partial Eta Squared Noncent. Parameter Observed Powerb
Pillai's trace .041 1.418a 1.000 33.000 .242 .041 1.418 .212
Wilks' lambda .959 1.418a 1.000 33.000 .242 .041 1.418 .212
Hotelling's trace .043 1.418a 1.000 33.000 .242 .041 1.418 .212
Roy's largest root .043 1.418a 1.000 33.000 .242 .041 1.418 .212
Each F tests the multivariate effect of length. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.
a. Exact statistic
b. Computed using alpha = .05
2. width
2. width - Estimates - August 19, 2020
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
width Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 -4.254 3.135 -10.632 2.125
2 -2.404 1.556 -5.569 .761
3 -7.434 4.781 -17.161 2.292
2. width
2. width - Pairwise Comparisons - August 19, 2020
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 12 rows
MEASURE_1 MEASURE_1
(I) width (J) width Mean Difference (I-J) Std. Error Sig.a 95% Confidence Interval for Differencea
Lower Bound Upper Bound
1 2 -1.850 1.660 .273 -5.228 1.528
3 3.180 1.812 .089 -.507 6.868
2 1 1.850 1.660 .273 -1.528 5.228
3 5.030 3.302 .137 -1.689 11.749
3 1 -3.180 1.812 .089 -6.868 .507
2 -5.030 3.302 .137 -11.749 1.689
Based on estimated marginal means
a. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).
2. width
2. width - Multivariate Tests - August 19, 2020
Multivariate TestsMultivariate Tests, table, 1 levels of column headers and 1 levels of row headers, table with 9 columns and 9 rows
  Value F Hypothesis df Error df Sig. Partial Eta Squared Noncent. Parameter Observed Powerb
Pillai's trace .092 1.623a 2.000 32.000 .213 .092 3.246 .317
Wilks' lambda .908 1.623a 2.000 32.000 .213 .092 3.246 .317
Hotelling's trace .101 1.623a 2.000 32.000 .213 .092 3.246 .317
Roy's largest root .101 1.623a 2.000 32.000 .213 .092 3.246 .317
Each F tests the multivariate effect of width. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.
a. Exact statistic
b. Computed using alpha = .05
3. length * width
3. length * width - Estimates - August 19, 2020
EstimatesEstimates, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 2 levels of row headers, table with 6 columns and 10 rows
MEASURE_1 MEASURE_1
length width Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 1 -3.967 2.805 -9.674 1.739
2 -2.329 1.477 -5.335 .676
3 -6.126 4.307 -14.889 2.637
2 1 -4.540 3.520 -11.701 2.621
2 -2.479 1.708 -5.954 .997
3 -8.742 5.307 -19.540 2.056
3. length * width
3. length * width - Pairwise Comparisons - August 19, 2020
Pairwise ComparisonsPairwise Comparisons, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 3 levels of row headers, table with 8 columns and 12 rows
MEASURE_1 MEASURE_1
width (I) length (J) length Mean Difference (I-J) Std. Error Sig.a 95% Confidence Interval for Differencea
Lower Bound Upper Bound
1 1 2 .573 1.094 .604 -1.652 2.798
2 1 -.573 1.094 .604 -2.798 1.652
2 1 2 .149 .722 .837 -1.319 1.618
2 1 -.149 .722 .837 -1.618 1.319
3 1 2 2.616 1.419 .074 -.272 5.504
2 1 -2.616 1.419 .074 -5.504 .272
Based on estimated marginal means  
a. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).  
3. length * width
3. length * width - Multivariate Tests - August 19, 2020
Multivariate TestsMultivariate Tests, table, 1 levels of column headers and 2 levels of row headers, table with 10 columns and 17 rows
width Value F Hypothesis df Error df Sig. Partial Eta Squared Noncent. Parameter Observed Powerb
1 Pillai's trace .008 .274a 1.000 33.000 .604 .008 .274 .080
Wilks' lambda .992 .274a 1.000 33.000 .604 .008 .274 .080
Hotelling's trace .008 .274a 1.000 33.000 .604 .008 .274 .080
Roy's largest root .008 .274a 1.000 33.000 .604 .008 .274 .080
2 Pillai's trace .001 .043a 1.000 33.000 .837 .001 .043 .055
Wilks' lambda .999 .043a 1.000 33.000 .837 .001 .043 .055
Hotelling's trace .001 .043a 1.000 33.000 .837 .001 .043 .055
Roy's largest root .001 .043a 1.000 33.000 .837 .001 .043 .055
3 Pillai's trace .093 3.396a 1.000 33.000 .074 .093 3.396 .432
Wilks' lambda .907 3.396a 1.000 33.000 .074 .093 3.396 .432
Hotelling's trace .103 3.396a 1.000 33.000 .074 .093 3.396 .432
Roy's largest root .103 3.396a 1.000 33.000 .074 .093 3.396 .432
Each F tests the multivariate simple effects of length within each level combination of the other effects shown. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.
a. Exact statistic
b. Computed using alpha = .05
4. length * width
4. length * width - Estimates - August 19, 2020
EstimatesEstimates, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 2 levels of row headers, table with 6 columns and 10 rows
MEASURE_1 MEASURE_1
length width Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 1 -3.967 2.805 -9.674 1.739
2 -2.329 1.477 -5.335 .676
3 -6.126 4.307 -14.889 2.637
2 1 -4.540 3.520 -11.701 2.621
2 -2.479 1.708 -5.954 .997
3 -8.742 5.307 -19.540 2.056
4. length * width
4. length * width - Pairwise Comparisons - August 19, 2020
Pairwise ComparisonsPairwise Comparisons, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 3 levels of row headers, table with 8 columns and 19 rows
MEASURE_1 MEASURE_1
length (I) width (J) width Mean Difference (I-J) Std. Error Sig.b 95% Confidence Interval for Differenceb
Lower Bound Upper Bound
1 1 2 -1.638 1.508 .285 -4.705 1.429
3 2.159 1.707 .215 -1.313 5.631
2 1 1.638 1.508 .285 -1.429 4.705
3 3.797 3.042 .221 -2.392 9.986
3 1 -2.159 1.707 .215 -5.631 1.313
2 -3.797 3.042 .221 -9.986 2.392
2 1 2 -2.061 1.902 .286 -5.931 1.808
3 4.202* 2.061 .050 .010 8.394
2 1 2.061 1.902 .286 -1.808 5.931
3 6.264 3.642 .095 -1.146 13.673
3 1 -4.202* 2.061 .050 -8.394 -.010
2 -6.264 3.642 .095 -13.673 1.146
Based on estimated marginal means  
*. The mean difference is significant at the .05 level.  
b. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).  
4. length * width
4. length * width - Multivariate Tests - August 19, 2020
Multivariate TestsMultivariate Tests, table, 1 levels of column headers and 2 levels of row headers, table with 10 columns and 13 rows
length Value F Hypothesis df Error df Sig. Partial Eta Squared Noncent. Parameter Observed Powerb
1 Pillai's trace .047 .786a 2.000 32.000 .464 .047 1.571 .172
Wilks' lambda .953 .786a 2.000 32.000 .464 .047 1.571 .172
Hotelling's trace .049 .786a 2.000 32.000 .464 .047 1.571 .172
Roy's largest root .049 .786a 2.000 32.000 .464 .047 1.571 .172
2 Pillai's trace .117 2.111a 2.000 32.000 .138 .117 4.222 .401
Wilks' lambda .883 2.111a 2.000 32.000 .138 .117 4.222 .401
Hotelling's trace .132 2.111a 2.000 32.000 .138 .117 4.222 .401
Roy's largest root .132 2.111a 2.000 32.000 .138 .117 4.222 .401
Each F tests the multivariate simple effects of width within each level combination of the other effects shown. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.
a. Exact statistic
b. Computed using alpha = .05
5. length * width
5. length * width - Estimates - August 19, 2020
EstimatesEstimates, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 2 levels of row headers, table with 6 columns and 10 rows
MEASURE_1 MEASURE_1
length width Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 1 -3.967 2.805 -9.674 1.739
2 -2.329 1.477 -5.335 .676
3 -6.126 4.307 -14.889 2.637
2 1 -4.540 3.520 -11.701 2.621
2 -2.479 1.708 -5.954 .997
3 -8.742 5.307 -19.540 2.056
5. length * width
5. length * width - Pairwise Comparisons - August 19, 2020
Pairwise ComparisonsPairwise Comparisons, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 3 levels of row headers, table with 8 columns and 12 rows
MEASURE_1 MEASURE_1
width (I) length (J) length Mean Difference (I-J) Std. Error Sig.a 95% Confidence Interval for Differencea
Lower Bound Upper Bound
1 1 2 .573 1.094 .604 -1.652 2.798
2 1 -.573 1.094 .604 -2.798 1.652
2 1 2 .149 .722 .837 -1.319 1.618
2 1 -.149 .722 .837 -1.618 1.319
3 1 2 2.616 1.419 .074 -.272 5.504
2 1 -2.616 1.419 .074 -5.504 .272
Based on estimated marginal means  
a. Adjustment for multiple comparisons: Bonferroni.  
5. length * width
5. length * width - Multivariate Tests - August 19, 2020
Multivariate TestsMultivariate Tests, table, 1 levels of column headers and 2 levels of row headers, table with 10 columns and 17 rows
width Value F Hypothesis df Error df Sig. Partial Eta Squared Noncent. Parameter Observed Powerb
1 Pillai's trace .008 .274a 1.000 33.000 .604 .008 .274 .080
Wilks' lambda .992 .274a 1.000 33.000 .604 .008 .274 .080
Hotelling's trace .008 .274a 1.000 33.000 .604 .008 .274 .080
Roy's largest root .008 .274a 1.000 33.000 .604 .008 .274 .080
2 Pillai's trace .001 .043a 1.000 33.000 .837 .001 .043 .055
Wilks' lambda .999 .043a 1.000 33.000 .837 .001 .043 .055
Hotelling's trace .001 .043a 1.000 33.000 .837 .001 .043 .055
Roy's largest root .001 .043a 1.000 33.000 .837 .001 .043 .055
3 Pillai's trace .093 3.396a 1.000 33.000 .074 .093 3.396 .432
Wilks' lambda .907 3.396a 1.000 33.000 .074 .093 3.396 .432
Hotelling's trace .103 3.396a 1.000 33.000 .074 .093 3.396 .432
Roy's largest root .103 3.396a 1.000 33.000 .074 .093 3.396 .432
Each F tests the multivariate simple effects of length within each level combination of the other effects shown. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.
a. Exact statistic
b. Computed using alpha = .05
6. length * width
6. length * width - Estimates - August 19, 2020
EstimatesEstimates, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 2 levels of row headers, table with 6 columns and 10 rows
MEASURE_1 MEASURE_1
length width Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 1 -3.967 2.805 -9.674 1.739
2 -2.329 1.477 -5.335 .676
3 -6.126 4.307 -14.889 2.637
2 1 -4.540 3.520 -11.701 2.621
2 -2.479 1.708 -5.954 .997
3 -8.742 5.307 -19.540 2.056
6. length * width
6. length * width - Pairwise Comparisons - August 19, 2020
Pairwise ComparisonsPairwise Comparisons, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 3 levels of row headers, table with 8 columns and 18 rows
MEASURE_1 MEASURE_1
length (I) width (J) width Mean Difference (I-J) Std. Error Sig.a 95% Confidence Interval for Differencea
Lower Bound Upper Bound
1 1 2 -1.638 1.508 .855 -5.440 2.164
3 2.159 1.707 .644 -2.146 6.463
2 1 1.638 1.508 .855 -2.164 5.440
3 3.797 3.042 .662 -3.875 11.469
3 1 -2.159 1.707 .644 -6.463 2.146
2 -3.797 3.042 .662 -11.469 3.875
2 1 2 -2.061 1.902 .859 -6.858 2.735
3 4.202 2.061 .149 -.995 9.399
2 1 2.061 1.902 .859 -2.735 6.858
3 6.264 3.642 .284 -2.922 15.449
3 1 -4.202 2.061 .149 -9.399 .995
2 -6.264 3.642 .284 -15.449 2.922
Based on estimated marginal means  
a. Adjustment for multiple comparisons: Bonferroni.  
6. length * width
6. length * width - Multivariate Tests - August 19, 2020
Multivariate TestsMultivariate Tests, table, 1 levels of column headers and 2 levels of row headers, table with 10 columns and 13 rows
length Value F Hypothesis df Error df Sig. Partial Eta Squared Noncent. Parameter Observed Powerb
1 Pillai's trace .047 .786a 2.000 32.000 .464 .047 1.571 .172
Wilks' lambda .953 .786a 2.000 32.000 .464 .047 1.571 .172
Hotelling's trace .049 .786a 2.000 32.000 .464 .047 1.571 .172
Roy's largest root .049 .786a 2.000 32.000 .464 .047 1.571 .172
2 Pillai's trace .117 2.111a 2.000 32.000 .138 .117 4.222 .401
Wilks' lambda .883 2.111a 2.000 32.000 .138 .117 4.222 .401
Hotelling's trace .132 2.111a 2.000 32.000 .138 .117 4.222 .401
Roy's largest root .132 2.111a 2.000 32.000 .138 .117 4.222 .401
Each F tests the multivariate simple effects of width within each level combination of the other effects shown. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.
a. Exact statistic
b. Computed using alpha = .05
7. length * width
7. length * width - Estimates - August 19, 2020
EstimatesEstimates, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 2 levels of row headers, table with 6 columns and 10 rows
MEASURE_1 MEASURE_1
length width Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 1 -3.967 2.805 -9.674 1.739
2 -2.329 1.477 -5.335 .676
3 -6.126 4.307 -14.889 2.637
2 1 -4.540 3.520 -11.701 2.621
2 -2.479 1.708 -5.954 .997
3 -8.742 5.307 -19.540 2.056
7. length * width
7. length * width - Pairwise Comparisons - August 19, 2020
Pairwise ComparisonsPairwise Comparisons, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 3 levels of row headers, table with 8 columns and 12 rows
MEASURE_1 MEASURE_1
width (I) length (J) length Mean Difference (I-J) Std. Error Sig.a 95% Confidence Interval for Differencea
Lower Bound Upper Bound
1 1 2 .573 1.094 .604 -1.652 2.798
2 1 -.573 1.094 .604 -2.798 1.652
2 1 2 .149 .722 .837 -1.319 1.618
2 1 -.149 .722 .837 -1.618 1.319
3 1 2 2.616 1.419 .074 -.272 5.504
2 1 -2.616 1.419 .074 -5.504 .272
Based on estimated marginal means  
a. Adjustment for multiple comparisons: Sidak.  
7. length * width
7. length * width - Multivariate Tests - August 19, 2020
Multivariate TestsMultivariate Tests, table, 1 levels of column headers and 2 levels of row headers, table with 10 columns and 17 rows
width Value F Hypothesis df Error df Sig. Partial Eta Squared Noncent. Parameter Observed Powerb
1 Pillai's trace .008 .274a 1.000 33.000 .604 .008 .274 .080
Wilks' lambda .992 .274a 1.000 33.000 .604 .008 .274 .080
Hotelling's trace .008 .274a 1.000 33.000 .604 .008 .274 .080
Roy's largest root .008 .274a 1.000 33.000 .604 .008 .274 .080
2 Pillai's trace .001 .043a 1.000 33.000 .837 .001 .043 .055
Wilks' lambda .999 .043a 1.000 33.000 .837 .001 .043 .055
Hotelling's trace .001 .043a 1.000 33.000 .837 .001 .043 .055
Roy's largest root .001 .043a 1.000 33.000 .837 .001 .043 .055
3 Pillai's trace .093 3.396a 1.000 33.000 .074 .093 3.396 .432
Wilks' lambda .907 3.396a 1.000 33.000 .074 .093 3.396 .432
Hotelling's trace .103 3.396a 1.000 33.000 .074 .093 3.396 .432
Roy's largest root .103 3.396a 1.000 33.000 .074 .093 3.396 .432
Each F tests the multivariate simple effects of length within each level combination of the other effects shown. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.
a. Exact statistic
b. Computed using alpha = .05
8. length * width
8. length * width - Estimates - August 19, 2020
EstimatesEstimates, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 2 levels of row headers, table with 6 columns and 10 rows
MEASURE_1 MEASURE_1
length width Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
1 1 -3.967 2.805 -9.674 1.739
2 -2.329 1.477 -5.335 .676
3 -6.126 4.307 -14.889 2.637
2 1 -4.540 3.520 -11.701 2.621
2 -2.479 1.708 -5.954 .997
3 -8.742 5.307 -19.540 2.056
8. length * width
8. length * width - Pairwise Comparisons - August 19, 2020
Pairwise ComparisonsPairwise Comparisons, table, Measure, MEASURE_1, 1 layers, 2 levels of column headers and 3 levels of row headers, table with 8 columns and 18 rows
MEASURE_1 MEASURE_1
length (I) width (J) width Mean Difference (I-J) Std. Error Sig.a 95% Confidence Interval for Differencea
Lower Bound Upper Bound
1 1 2 -1.638 1.508 .635 -5.430 2.153
3 2.159 1.707 .516 -2.133 6.451
2 1 1.638 1.508 .635 -2.153 5.430
3 3.797 3.042 .527 -3.853 11.447
3 1 -2.159 1.707 .516 -6.451 2.133
2 -3.797 3.042 .527 -11.447 3.853
2 1 2 -2.061 1.902 .636 -6.844 2.721
3 4.202 2.061 .141 -.981 9.385
2 1 2.061 1.902 .636 -2.721 6.844
3 6.264 3.642 .258 -2.896 15.423
3 1 -4.202 2.061 .141 -9.385 .981
2 -6.264 3.642 .258 -15.423 2.896
Based on estimated marginal means  
a. Adjustment for multiple comparisons: Sidak.  
8. length * width
8. length * width - Multivariate Tests - August 19, 2020
Multivariate TestsMultivariate Tests, table, 1 levels of column headers and 2 levels of row headers, table with 10 columns and 13 rows
length Value F Hypothesis df Error df Sig. Partial Eta Squared Noncent. Parameter Observed Powerb
1 Pillai's trace .047 .786a 2.000 32.000 .464 .047 1.571 .172
Wilks' lambda .953 .786a 2.000 32.000 .464 .047 1.571 .172
Hotelling's trace .049 .786a 2.000 32.000 .464 .047 1.571 .172
Roy's largest root .049 .786a 2.000 32.000 .464 .047 1.571 .172
2 Pillai's trace .117 2.111a 2.000 32.000 .138 .117 4.222 .401
Wilks' lambda .883 2.111a 2.000 32.000 .138 .117 4.222 .401
Hotelling's trace .132 2.111a 2.000 32.000 .138 .117 4.222 .401
Roy's largest root .132 2.111a 2.000 32.000 .138 .117 4.222 .401
Each F tests the multivariate simple effects of width within each level combination of the other effects shown. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.
a. Exact statistic
b. Computed using alpha = .05
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