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niversity of North Texas Dr. J. Kyle Roberts © 2004 Unit 9: Planned Contrast ANOVA Lesson 1: Merging Regression and ANOVA EDER 6010: Statistics for Educational Research Dr. J. Kyle Roberts University of North Texas Planned Contrast Next Slide

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Page 1: Unit 9 lesson 1

University of North Texas Dr. J. Kyle Roberts © 2004

Unit 9: Planned Contrast ANOVA

Lesson 1: Merging Regression and ANOVA

EDER 6010: Statistics for Educational Research

Dr. J. Kyle Roberts

University of North Texas

Planned Contrast

Next Slide

Page 2: Unit 9 lesson 1

University of North Texas Dr. J. Kyle Roberts © 2004

Being a “Not-Smart” Researcher

One-Way 3 Level ANOVA•Mean IQ

•Blondes = 105•Brunettes = 107•Redheads = 111.5

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453.2

Page 3: Unit 9 lesson 1

University of North Texas Dr. J. Kyle Roberts © 2004

Being a “Smart” Researcher

H0: MeanBlonde=MeanBrunette=MeanRedhead

•Blondes = 105

•Brunettes = 107

•Redheads = 111.5

H0:MBlonde & MBrunette=MRed

Probably is statistically significantly different

H0:MBlonde=MBrunette

Probably not statistically significantly different

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Page 4: Unit 9 lesson 1

University of North Texas Dr. J. Kyle Roberts © 2004

Creating Contrast Variables

Mean Contrast 1 Contrast 2

Blondes 105 1 1

Brunettes 107 -1 1

Redheads 111.5 0 -2

Contrasts reflect the associations that we want to test

Contrast 1 tests H0: Mblondes=Mbrunettes

Contrast 2 tests H0: Mblondes & brunettes=Mredheads

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Maximum number of contrasts = K –1

Page 5: Unit 9 lesson 1

University of North Texas Dr. J. Kyle Roberts © 2004

Practice Contrast VariablesC1 C2 C3 C4

White 1 0 1 1

Black -1 0 1 -3

Asian 0 1 -4 1

Hispanic 0 1 1 0

Native American

0 -2 1 1

C1 – H0: Mwhite=Mblack

C2 – H0: Masian and hisp.=Mnat.amer. C4 – H0: Mw,a,na.=Mb

C3 – H0: Mw,b,h,na=Ma

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Page 6: Unit 9 lesson 1

University of North Texas Dr. J. Kyle Roberts © 2004

Back to “IQ” – “Hair” Example

3210

210

:2

:1

XXHc

XXHc

and

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Page 7: Unit 9 lesson 1

University of North Texas Dr. J. Kyle Roberts © 2004

Regression as ANOVAAnalyze Regression Linear

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Page 8: Unit 9 lesson 1

University of North Texas Dr. J. Kyle Roberts © 2004

Planned Contrast ANOVA Output

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Page 9: Unit 9 lesson 1

University of North Texas Dr. J. Kyle Roberts © 2004

Planned Contrast ANOVA Output (cont.)

SSc2= 88.667 – 8.0 = 80.667

F-crit on 1 and 9 df = 5.12

Y

N

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SSc2=SS2 regression – SS1 regression

Page 10: Unit 9 lesson 1

University of North Texas Dr. J. Kyle Roberts © 2004

Smart vs. Not-Smart Researchers

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Page 11: Unit 9 lesson 1

University of North Texas Dr. J. Kyle Roberts © 2004

A New Example

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You will have 5 “Blocks.” C1 in Block 1; C2 in Block 2; etc.

Page 12: Unit 9 lesson 1

University of North Texas Dr. J. Kyle Roberts © 2004

SPSS Output for “New Example”

SSc2=.333 - .250

SSc3=.375 - .333

SSc4=.400 - .375

SSc5=370.417 - .400

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Page 13: Unit 9 lesson 1

University of North Texas Dr. J. Kyle Roberts © 2004

Results for “New Example”

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F-crit on 1 and 6 df = 5.99

Page 14: Unit 9 lesson 1

University of North Texas Dr. J. Kyle Roberts © 2004

“Other” Examples

C1 C2 C3 C4

Group 1 1 0 1 -1

Group 2 -1 0 1 -1

Group 3 0 0 0 4

Group 4 0 1 -1 -1

Group 5 0 -1 -1 -1

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Page 15: Unit 9 lesson 1

University of North Texas Dr. J. Kyle Roberts © 2004

Unit 9: Planned Contrast ANOVA

Lesson 1: Merging Regression and ANOVA

EDER 6010: Statistics for Educational Research

Dr. J. Kyle Roberts

University of North Texas

Planned Contrast