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: Unbalanced 2-Way (Fixed Effects) ANOVA Dataset: celebrityendorse_attention.csv Source: P.-S. Wei, H.-P. Lu (2013). An examination of the Celebrity Endorsements and Online Customer Reviews Influence

: Unbalanced 2-Way (Fixed Effects) ANOVA

Dataset: celebrityendorse_attention.csv

Source: P.-S. Wei, H.-P. Lu (2013). "An examination of the Celebrity

Endorsements and Online Customer Reviews Influence Female Consumers'

Shopping Behavior," Computers in Human Behavior, Vol. 29, pp. 193-201.

Description: Experiment with 2-factors: Product (1=Shoes, 2=Ink Toner)

and Endorser (1=Celebrity, 2=Online customer). Completely Randomized

(Between Subjects) Design. Data simulated to match trt means and SDs.

Response is subjects' attention score (average of 3 1-5 responses).

Variable names:

trt_group /* 1=shoes/celeb, 2=shoes/online, 3=toner/celeb, 4=toner/online

product /* 1= shoes, 2=ink toner */

endorser /* 1=celebrity, 2=online customer */

shoe /* 1=shoe, 0=toner */

celebrity /* 1=celebrity, 0=online customer */

attention /* response variable */

  • Fit the 2-Way ANOVA model as a regression model with X1 = 1 if shoes, -1 if Toner; and X2 = 1 if Celebrity, -1 if online customer. Test for interaction, and main effects.
  • Use the aov function in R. Test for main interaction and main effects. (use the contrasts=c("contr.sum", "contr.poly") option)
  • Compare the results.

R code

celeb <- read.csv( "http://www.stat.ufl.edu/~winner/data/celebrityendorse_attention.csv") attach(celeb); names(celeb)

X1 <- ifelse(shoe==1, 1, -1) X2 <- ifelse(celebrity==1, 1, -1)

options(contrasts=c("contr.sum", "contr.poly"))

Datat :

trt_group

product

endorser

shoe

celebrity

attention

1

1

1

1

1

2.32

1

1

1

1

1

3.80

1

1

1

1

1

3.76

1

1

1

1

1

3.80

1

1

1

1

1

4.49

1

1

1

1

1

3.85

1

1

1

1

1

2.02

1

1

1

1

1

2.66

1

1

1

1

1

3.92

1

1

1

1

1

3.48

1

1

1

1

1

4.00

1

1

1

1

1

3.57

1

1

1

1

1

2.81

1

1

1

1

1

4.67

1

1

1

1

1

2.84

1

1

1

1

1

4.42

1

1

1

1

1

2.82

1

1

1

1

1

2.76

1

1

1

1

1

2.53

1

1

1

1

1

2.66

1

1

1

1

1

2.91

1

1

1

1

1

2.87

1

1

1

1

1

2.45

1

1

1

1

1

2.10

1

1

1

1

1

2.62

1

1

1

1

1

4.34

1

1

1

1

1

3.52

1

1

1

1

1

4.65

1

1

1

1

1

4.40

1

1

1

1

1

2.12

1

1

1

1

1

3.31

1

1

1

1

1

2.76

1

1

1

1

1

2.87

1

1

1

1

1

3.46

1

1

1

1

1

2.51

1

1

1

1

1

4.20

1

1

1

1

1

2.57

1

1

1

1

1

2.74

1

1

1

1

1

4.87

1

1

1

1

1

4.33

1

1

1

1

1

3.60

1

1

1

1

1

3.87

1

1

1

1

1

2.89

2

1

2

1

0

3.26

2

1

2

1

0

2.34

2

1

2

1

0

2.89

2

1

2

1

0

3.44

2

1

2

1

0

2.83

2

1

2

1

0

2.07

2

1

2

1

0

3.71

2

1

2

1

0

1.54

2

1

2

1

0

2.28

2

1

2

1

0

3.56

2

1

2

1

0

2.89

2

1

2

1

0

1.79

2

1

2

1

0

2.89

2

1

2

1

0

2.86

2

1

2

1

0

3.67

2

1

2

1

0

1.86

2

1

2

1

0

3.98

2

1

2

1

0

4.03

2

1

2

1

0

1.44

2

1

2

1

0

2.30

2

1

2

1

0

1.35

2

1

2

1

0

2.06

2

1

2

1

0

3.53

2

1

2

1

0

2.28

2

1

2

1

0

2.91

2

1

2

1

0

1.47

2

1

2

1

0

3.08

2

1

2

1

0

1.69

2

1

2

1

0

4.11

2

1

2

1

0

1.35

2

1

2

1

0

3.77

2

1

2

1

0

1.59

2

1

2

1

0

2.94

2

1

2

1

0

2.52

2

1

2

1

0

1.53

2

1

2

1

0

2.32

2

1

2

1

0

3.41

2

1

2

1

0

4.22

2

1

2

1

0

2.79

2

1

2

1

0

1.76

2

1

2

1

0

3.02

2

1

2

1

0

1.92

2

1

2

1

0

4.13

2

1

2

1

0

2.53

3

2

1

0

1

2.55

3

2

1

0

1

2.13

3

2

1

0

1

4.16

3

2

1

0

1

2.15

3

2

1

0

1

4.17

3

2

1

0

1

2.06

3

2

1

0

1

2.06

3

2

1

0

1

1.98

3

2

1

0

1

3.10

3

2

1

0

1

2.52

3

2

1

0

1

1.77

3

2

1

0

1

2.55

3

2

1

0

1

3.74

3

2

1

0

1

1.79

3

2

1

0

1

3.25

3

2

1

0

1

2.47

3

2

1

0

1

2.26

3

2

1

0

1

2.06

3

2

1

0

1

2.59

3

2

1

0

1

2.12

3

2

1

0

1

2.05

3

2

1

0

1

2.89

3

2

1

0

1

1.80

3

2

1

0

1

3.66

3

2

1

0

1

1.97

3

2

1

0

1

4.31

3

2

1

0

1

2.03

3

2

1

0

1

2.30

3

2

1

0

1

4.21

3

2

1

0

1

4.30

3

2

1

0

1

2.46

3

2

1

0

1

2.03

3

2

1

0

1

3.89

3

2

1

0

1

3.74

3

2

1

0

1

4.21

3

2

1

0

1

4.43

3

2

1

0

1

4.29

3

2

1

0

1

3.03

3

2

1

0

1

2.47

3

2

1

0

1

2.39

3

2

1

0

1

3.08

3

2

1

0

1

3.06

3

2

1

0

1

2.57

3

2

1

0

1

4.34

3

2

1

0

1

3.44

3

2

1

0

1

2.04

4

2

2

0

0

4.22

4

2

2

0

0

2.65

4

2

2

0

0

1.22

4

2

2

0

0

2.05

4

2

2

0

0

2.33

4

2

2

0

0

1.60

4

2

2

0

0

2.93

4

2

2

0

0

4.04

4

2

2

0

0

2.34

4

2

2

0

0

2.97

4

2

2

0

0

2.92

4

2

2

0

0

4.02

4

2

2

0

0

3.18

4

2

2

0

0

1.50

4

2

2

0

0

4.06

4

2

2

0

0

3.18

4

2

2

0

0

1.88

4

2

2

0

0

3.85

4

2

2

0

0

2.23

4

2

2

0

0

2.90

4

2

2

0

0

4.72

4

2

2

0

0

2.66

4

2

2

0

0

2.00

4

2

2

0

0

1.90

4

2

2

0

0

3.63

4

2

2

0

0

4.69

4

2

2

0

0

2.85

4

2

2

0

0

3.94

4

2

2

0

0

3.21

4

2

2

0

0

4.64

4

2

2

0

0

4.02

4

2

2

0

0

3.05

4

2

2

0

0

3.29

4

2

2

0

0

2.07

4

2

2

0

0

2.13

4

2

2

0

0

1.35

4

2

2

0

0

3.17

4

2

2

0

0

2.07

4

2

2

0

0

1.12

4

2

2

0

0

3.26

4

2

2

0

0

3.01

4

2

2

0

0

4.19

4

2

2

0

0

1.22

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