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GLM Pretest Recall BY Gudiance /WSFACTOR=Time 2 Polynomial /METHOD=SSTYPE(3) /EMMEANS=TABLES(OVERALL) /EMMEANS=TABLES(Time) COMPARE ADJ(LSD) /EMMEANS=TABLES(Gudiance) COMPARE ADJ(LSD) /EMMEANS=TABLES(Gudiance*Time) /PRINT=DESCRIPTIVE HOMOGENEITY /CRITERIA=ALPHA(.05) /WSDESIGN=Time /DESIGN=Gudiance.

General Linear Model

Notes

Output Created Comments Input Data

Active Dataset Filter Weight Split File N of Rows in Working Data File

Missing Value Handling Definition of Missing

Cases Used

14-APR-2020 18:05:...

/Users/kiracarbonneau/ Desktop/Kira_Disseratio n(1) (3).sav

DataSet1 < n o n e > < n o n e > < n o n e >

7 2

User-defined missing values are treated as missing.

Statistics are based on all cases with valid data for all variables in the model.

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Notes

Syntax

Resources Processor Time Elapsed Time

GLM Pretest Recall BY Gudiance /WSFACTOR=Time 2 Polynomial /METHOD=SSTYPE(3) /EMMEANS=TABLES (OVERALL) /EMMEANS=TABLES (Time) COMPARE ADJ (LSD) /EMMEANS=TABLES (Gudiance) COMPARE ADJ(LSD) /EMMEANS=TABLES (Gudiance*Time) /PRINT=DESCRIPTIVE HOMOGENEITY /CRITERIA=ALPHA(.05) /WSDESIGN=Time /DESIGN=Gudiance.

00:00:00.02 00:00:00.00

Within-Subjects Factors

Measure: MEASURE_1Measure: MEASURE_1Measure:

Time

Measure: MEASURE_1 Dependent

Variable

1 2

Pretest Recall

MEASURE_1Measure: MEASURE_1Measure: MEASURE_1

Between-Subjects Factors Value Label N

Gudiance 0 1

Low 3 6 High 3 6

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Descriptive Statistics

Gudiance Mean Std. Deviation N

Pretest_% Low High Total

Recall_% Low High Total

.633333 .1771019 3 6

.646296 .1405833 3 6

.639815 .1588928 7 2

.413889 .1310216 3 6

.690394 .1392896 3 6

.552141 .1934154 7 2

Box's Test of Equality of Covariance

Matrices a

Box's M F df1 df2 Sig.

2 . 7 8 6 . 9 0 0

3 882000.000

. 4 4 0 Tests the null hypothesis that the observed covariance matrices of the dependent variables are equal across groups.

Design: Intercept + Gudiance Within Subjects Design: Time

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Multivariate Testsa

Effect Value F Hypothesis df Error df Sig.

Time Pillai's Trace

Wilks' Lambda

Hotelling's Trace

Roy's Largest Root

Time * Gudiance Pillai's Trace

Wilks' Lambda

Hotelling's Trace

Roy's Largest Root

. 2 8 6 28.059 b 1 . 0 0 0 70.000 . 0 0 0

. 7 1 4 28.059 b 1 . 0 0 0 70.000 . 0 0 0

. 4 0 1 28.059 b 1 . 0 0 0 70.000 . 0 0 0

. 4 7 5 63.382 b 1 . 0 0 0 70.000 . 0 0 0

. 5 2 5 63.382 b 1 . 0 0 0 70.000 . 0 0 0

. 9 0 5 63.382 b 1 . 0 0 0 70.000 . 0 0 0

Design: Intercept + Gudiance Within Subjects Design: Time

Exact statisticb.

Mauchly's Test of Sphericity a

Measure: MEASURE_1Measure: MEASURE_1Measure: MEASURE_1

Within Subjects Effect

MEASURE_1

Mauchly's W Approx. Chi-

Square df Sig.

Epsilonb

Greenhouse- Geisser

Time 1 . 0 0 0 . 0 0 0 0 . 1 . 0 0 0 1 . 0 0 0

Measure: MEASURE_1Measure: MEASURE_1

Mauchly's Test of Sphericity a

Measure: MEASURE_1Measure: MEASURE_1Measure: MEASURE_1

Within Subjects Effect

Epsilonb

Huynh-Feldt Lower-bound

Time 1 . 0 0 0 1 . 0 0 0

Measure: MEASURE_1Measure: MEASURE_1

Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix.

Design: Intercept + Gudiance Within Subjects Design: Time

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.

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Tests of Within-Subjects Effects Measure: MEASURE_1Measure: MEASURE_1Measure: MEASURE_1

Source Type III Sum of

Squares df Mean Square F

Time Sphericity Assumed Greenhouse-Geisser Huynh-Feldt Lower-bound

Time * Gudiance Sphericity Assumed Greenhouse-Geisser Huynh-Feldt Lower-bound

Error(Time) Sphericity Assumed Greenhouse-Geisser Huynh-Feldt Lower-bound

. 2 7 7 1 . 2 7 7 28.059 . 0 0 0

. 2 7 7 1 . 0 0 0 . 2 7 7 28.059 . 0 0 0

. 6 2 5 1 . 6 2 5 63.382 . 0 0 0

. 6 2 5 1 . 0 0 0 . 6 2 5 63.382 . 0 0 0

. 6 9 0 7 0 . 0 1 0

. 6 9 0 70.000 . 0 1 0

Measure: MEASURE_1Measure: MEASURE_1

Tests of Within-Subjects Effects Measure: MEASURE_1Measure: MEASURE_1Measure: MEASURE_1

Source Sig.

Time Sphericity Assumed Greenhouse-Geisser Huynh-Feldt Lower-bound

Time * Gudiance Sphericity Assumed Greenhouse-Geisser Huynh-Feldt Lower-bound

Error(Time) Sphericity Assumed Greenhouse-Geisser Huynh-Feldt Lower-bound

. 0 0 0

Measure: MEASURE_1Measure: MEASURE_1

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Tests of Within-Subjects Contrasts Measure: MEASURE_1Measure: MEASURE_1Measure: MEASURE_1

Source Time Type III Sum of

Squares df Mean Square F Sig.

Time Linear Time * Gudiance Linear Error(Time) Linear

. 2 7 7 1 . 2 7 7 28.059 . 0 0 0

. 6 2 5 1 . 6 2 5 63.382 . 0 0 0

. 6 9 0 7 0 . 0 1 0

Measure: MEASURE_1Measure: MEASURE_1

Levene's Test of Equality of Error Variances a

Levene Statistic df1 df2 Sig.

Pretest_% Based on Mean Based on Median Based on Median and with adjusted df

Based on trimmed mean

Recall_% Based on Mean Based on Median Based on Median and with adjusted df

Based on trimmed mean

1 . 5 5 0 1 7 0 . 2 1 7 1 . 1 3 9 1 7 0 . 2 9 0 1 . 1 3 9 1 63.337 . 2 9 0

1 . 5 1 5 1 7 0 . 2 2 2

. 3 2 0 1 7 0 . 5 7 4

. 5 4 3 1 7 0 . 4 6 4

. 5 4 3 1 69.673 . 4 6 4

. 3 8 0 1 7 0 . 5 4 0

Tests the null hypothesis that the error variance of the dependent variable is equal across groups.

Design: Intercept + Gudiance Within Subjects Design: Time

Tests of Between-Subjects Effects Measure: MEASURE_1Measure: MEASURE_1 Transformed Variable: AverageTransformed Variable:

Source

Transformed Variable: Average Type III Sum of

Squares df Mean Square F Sig.

Intercept Gudiance Error

51.147 1 51.147 1504.939 . 0 0 0 . 7 5 4 1 . 7 5 4 22.189 . 0 0 0

2 . 3 7 9 7 0 . 0 3 4

Measure: MEASURE_1 Transformed Variable: Average

Estimated Marginal Means

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1. Grand Mean Measure: MEASURE_1Measure: MEASURE_1Measure: MEASURE_1

Mean Std. Error 95% Confidence Interval

Lower Bound Upper Bound

. 5 9 6 . 0 1 5 . 5 6 5 . 6 2 7

Measure: MEASURE_1Measure: MEASURE_1

2. Time

Estimates Measure: MEASURE_1Measure: MEASURE_1Measure:

Time

Measure: MEASURE_1

Mean Std. Error 95% Confidence Interval

Lower Bound Upper Bound

1 2

. 6 4 0 . 0 1 9 . 6 0 2 . 6 7 7

. 5 5 2 . 0 1 6 . 5 2 0 . 5 8 4

Measure: MEASURE_1Measure: MEASURE_1

Pairwise Comparisons Measure: MEASURE_1Measure: MEASURE_1Measure: MEASURE_1

(I) Time (J) Time

MEASURE_1

Mean Difference (I-J) Std. Error Sig.b

95% Confidence Interval for Differenceb

Lower Bound Upper Bound

1 2

2 1

. 0 8 8 * . 0 1 7 . 0 0 0 . 0 5 5 . 1 2 1

- . 0 8 8 * . 0 1 7 . 0 0 0 - . 1 2 1 - . 0 5 5

Measure: MEASURE_1Measure: MEASURE_1

Based on estimated marginal means The mean difference is significant at the .05 level.* . Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).b.

Multivariate Tests

Value F Hypothesis df Error df Sig.

Pillai's trace

Wilks' lambda

Hotelling's trace

Roy's largest root

. 2 8 6 28.059 a 1 . 0 0 0 70.000 . 0 0 0

. 7 1 4 28.059 a 1 . 0 0 0 70.000 . 0 0 0

. 4 0 1 28.059 a 1 . 0 0 0 70.000 . 0 0 0

. 4 0 1 28.059 a 1 . 0 0 0 70.000 . 0 0 0 Each F tests the multivariate effect of Time. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.

Exact statistica.

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3. Gudiance

Estimates Measure: MEASURE_1Measure: MEASURE_1Measure: MEASURE_1

Gudiance

Measure: MEASURE_1

Mean Std. Error 95% Confidence Interval

Lower Bound Upper Bound

Low High

. 5 2 4 . 0 2 2 . 4 8 0 . 5 6 7

. 6 6 8 . 0 2 2 . 6 2 5 . 7 1 2

Measure: MEASURE_1Measure: MEASURE_1

Pairwise Comparisons Measure: MEASURE_1Measure: MEASURE_1Measure: MEASURE_1

(I) Gudiance (J) Gudiance Mean

Difference (I-J) Std. Error Sig.b

95% Confidence Interval for Differenceb

Lower Bound Upper Bound

Low High

High Low

- . 1 4 5 * . 0 3 1 . 0 0 0 - . 2 0 6 - . 0 8 3

. 1 4 5 * . 0 3 1 . 0 0 0 . 0 8 3 . 2 0 6

Measure: MEASURE_1Measure: MEASURE_1

Based on estimated marginal means The mean difference is significant at the .05 level.* . Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).b.

Univariate Tests Measure: MEASURE_1Measure: MEASURE_1Measure: MEASURE_1Measure: MEASURE_1

Sum of Squares df Mean Square F Sig.

Contrast Error

. 3 7 7 1 . 3 7 7 22.189 . 0 0 0 1 . 1 9 0 7 0 . 0 1 7

Measure: MEASURE_1Measure: MEASURE_1

The F tests the effect of Gudiance. This test is based on the linearly independent pairwise comparisons among the estimated marginal means.

4. Gudiance * Time Measure: MEASURE_1Measure: MEASURE_1Measure: MEASURE_1

Gudiance Time

MEASURE_1

Mean Std. Error 95% Confidence Interval

Lower Bound Upper Bound

Low 1 2

High 1 2

. 6 3 3 . 0 2 7 . 5 8 0 . 6 8 6

. 4 1 4 . 0 2 3 . 3 6 9 . 4 5 9

. 6 4 6 . 0 2 7 . 5 9 3 . 6 9 9

. 6 9 0 . 0 2 3 . 6 4 5 . 7 3 5

Measure: MEASURE_1Measure: MEASURE_1

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