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Mixed Models ANOVA Within-Subjects & Between-Subjects

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)

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Mixed Models ANOVA Within-Subjects & Between-Subjects

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  1. Mixed Models ANOVAWithin-Subjects &Between-Subjects Chapter 14

  2. Research Designs • Between – Between (2 between subjects factors) • Mixed Design (1 between, 1 within subjects factor) • Within – Within (2 within subjects factors) • The purpose of this experiment was to determine the effects of testing mode (treadmill, bike) and gender (male, female) on maximum VO2. • Testing mode is a within subjects factor with 2 levels • Gender is a between subjects factor with 2 levels • Maximum VO2 is the dependent variable.

  3. The Effects of Gender, Looks, Charisma on Attitude Create a categorical variable for all Between-Subjects Factors. Gender (1 – Male, 2 – Female)

  4. Use GLM – Repeated Measures

  5. Add Within Subjects Factors Click Define

  6. Options Button Check homogeneity of variance if you have a between subjects factor. Choose the Sidak post hoc test.

  7. Plots

  8. Simple Effects /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. Click Paste, then Window to view Syntax Window

  9. Verify 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 one between-subjects factor Gender (male, female) was used determine the effects of personality, looks and gender on attitude.

  10. Output: Descriptives Check homogeneity of covariance for mixed models. The groups do NOT have equal Covariance, Box’s Test of Equality F(45,1064) = 1.53, p = .005 Sphericity is not violated

  11. 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 No main effect for Gender F(1,42) = 2.032, p = .161. Sig. main effect for Gatorade F(2,42) = 20.065, p = .000 Sig. interaction between Gender and Gatorade dose F(2,42) = 11.911, p = .000

  12. Between Subjects Effects The groups have equal variance. No difference in gender F(1,18) = .005, p = .946

  13. Post hoc for Personality Main Effect They are all different from each other Gender F(1,42) = 2.032, p = .161

  14. Post hoc for Looks Main Effects They are all different from each other

  15. Simple Effects for Gender x Personality Males high charisma are different from females with high charisma. Males low charisma are different from females with low charisma.

  16. Homework MONDAY 11 / 29 1:00 – 3:00 PM Stat Consulting In class assignment: analyze Practice File 1 and Practice File 2.

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