Mixed Models ANOVA Within-Subjects & Between-Subjects
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Mixed Models ANOVA Mixed Models ANOVA Within-Subjects Within-Subjects & & Between-Subjects Between-Subjects Chapter 14 Chapter 14
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Mixed Models ANOVA Within-Subjects & Between-Subjects. Chapter 14. Research Designs. Between – Between (2 between subjects factors) Mixed Design (1 between, 1 within subjects factor) Within – Within (2 within subjects factors) - PowerPoint PPT Presentation
Transcript of Mixed Models ANOVA Within-Subjects & Between-Subjects
Mixed Models ANOVAMixed Models ANOVAWithin-Subjects Within-Subjects
&&Between-SubjectsBetween-Subjects
Chapter 14Chapter 14
Research DesignsResearch Designs
Between – Between (2 between subjects factors)Between – Between (2 between subjects factors) Mixed Design (1 between, 1 within subjects factor)Mixed Design (1 between, 1 within subjects factor) Within – Within (2 within subjects factors)Within – Within (2 within subjects factors) The purpose of this experiment was to determine The purpose of this experiment was to determine
the effects of testing mode (treadmill, bike) and the effects of testing mode (treadmill, bike) and gender (male, female) on maximum VOgender (male, female) on maximum VO22..
Testing mode is a within subjects factor with 2 levelsTesting mode is a within subjects factor with 2 levelsGender is a between subjects factor with 2 levelsGender is a between subjects factor with 2 levelsMaximum VOMaximum VO22 is the dependent variable. is the dependent variable.
The Effects of Gender, Looks, Charisma on AttitudeThe Effects of Gender, Looks, Charisma on Attitude
Create a categorical variable for all Between-Subjects Factors.
Gender (1 – Male, 2 – Female)
Use GLM – Repeated MeasuresUse GLM – Repeated Measures
Add Within Subjects FactorsAdd Within Subjects Factors
Click Define
Options ButtonOptions Button
Check homogeneity of variance if you have a between subjects factor.
Choose the Sidak post hoc test.
PlotsPlots
Horizontal Axis
Separate Lines
Separate Plots
Personality Looks Gender
Looks Gender Personality
Gender Personality Looks
Personality Looks
Personality Gender
Looks Gender
Simple EffectsSimple Effects
Click Paste, then Window to view Syntax Window
/EMMEANS=TABLES(gender*Personality) COMPARE(gender) ADJ(SIDAK) /EMMEANS=TABLES(Personality*gender) COMPARE(Personality) ADJ(SIDAK) /EMMEANS=TABLES(gender*Looks) COMPARE(gender) ADJ(SIDAK) /EMMEANS=TABLES(Looks*gender) COMPARE(Looks) ADJ(SIDAK) /EMMEANS=TABLES(Personality*Looks) COMPARE(Personality) ADJ(SIDAK) /EMMEANS=TABLES(Looks*Personality) COMPARE(Looks) ADJ(SIDAK) /EMMEANS=TABLES(gender*Personality*Looks) Compare(gender) ADJ(SIDAK) /EMMEANS=TABLES(Personality*Looks*gender) Compare(Personality) ADJ(SIDAK) /EMMEANS=TABLES(Looks*gender*Personality) Compare(Looks) ADJ(SIDAK)Enter the first interaction term in the Compare ( ).Then switch the order.
Verify the ModelVerify the Model
A 2 x 3 x 3 repeated measures ANVOVA with two within-subjects factors Personality (high, some, dull) and Looks (attractive, average, ugly) and onebetween-subjects factor Gender (male, female) was used determine the effects of personality,looks and gender on attitude.
Output: DescriptivesOutput: Descriptives
The groups do NOT have equal Covariance, Box’s Test of Equality F(45,1064) = 1.53, p = .005
Check homogeneity of covariance for mixed models.
Sphericity is not violated
No main effect for Gender F(1,42) = 2.032, p = .161.Sig. main effect for Gatorade F(2,42) = 20.065, p = .000Sig. interaction between Gender and Gatorade dose F(2,42) = 11.911, p = .000
Per. F(2,36) = 328, p = .000
P x G F(2,36) = 62, p=.000
Look F(2,36) = 423, p=.000
L x G F(2,36)=80, p=.000
P x L F(4,72)=36, p=.000
PxLxG F(4,72)=24, p=.000
Between Subjects EffectsBetween Subjects Effects
The groups have equal variance.
No difference in gender
F(1,18) = .005, p = .946
Post hoc for Personality Main EffectPost hoc for Personality Main Effect
Gender F(1,42) = 2.032, p = .161
They are all different from each other
Post hoc for Looks Main EffectsPost hoc for Looks Main Effects
They are all different from each other
Simple Effects for Simple Effects for Gender x PersonalityGender x Personality
Males high charisma are different from females with high charisma.
Males low charisma are different from females with low charisma.
HomeworkHomework
MONDAY 11 / 29 1:00 – 3:00 PM Stat Consulting
In class assignment: analyze Practice File 1 and Practice File 2.
