Animal Welfare

Summary

Psychometric development found 4 dimensions for the Animal Welfare (AW) scale, using all 24 items. By “found”, I mean the most stable solution when one uses of cross-validation to resample both persons and items, and when you bootstrap it all 500 times.

Interestingly, the 4 factor solution very enlightening. I interpreted the output and suggested names for each factor (based on item content), but these are just suggestions. The four latent factors seem to be:

  • Animal Usurpation
    • Refers to one’s endorsement on humans’ domination over animals. This factor is substantively close to Speciesism in the sense that AU refers to attitudes/beliefs and specieism to Morality. Nomothetically, as in an nomological network (which I estimate below: see “Exploring dimensionality - with Speciesism”), most Speciesism cluster together with AU.
  • Animal Rights Policy Preferences (or Government Action/Intervention)
    • Refers to one’s endorsement of policy preferences protecting the rights of non-human animals
  • Personal Importance
    • Refers to one’s interest on Animal Welfare issues, and personal involvement/interest.
  • Consumer Activism or Ethical consumption or Buycotting (as political actvism)
    • Refers ton one’s tendency to engage on consumer-based political actvism (also called Buycotting) which entails support for towards companies/products that treat animals ethically.

For a better visualization of this, please see the picture below.

I applied psychometric development to both the 24 items, as well as the 19. The results are the same. Both solutions fit really well via CFA and are very justifiable psychometrically. We can still sum up (or take the means) of all the items.

I used these techniques:

  • Parallel Analysis
  • Exploratory Factor Analysis
  • Confirmatory Factor Analysis
  • Exploratory Graphical Analysis
  • Network Analysis









1. Correlation Matrix of Animal Welfare

1.1. Per facet

1.2. All together

1.3. All together with criterion Variables

1.4. All together with all criterion Variables

1.5. Deleted variables with all criterion Variables









2. Dimensionality

2.1 Parallel Analysis

## Parallel analysis suggests that the number of factors =  5  and the number of components =  NA

2.2 Exploratory Factor Analysis (2 factors)

Fit indices of EFA
RMSEA TLI RMS CFI
0.09 0.82 0.06 0.85
EFA [2D] Summary
F1.loadings F2.loadings communality uniquenesses complexity
P1R 0.66 0.48 0.52 1.02
P2 0.61 0.54 0.46 1.20
P3R 0.53 0.27 0.73 1.00
P4 0.45 0.36 0.50 0.50 1.91
P5R 0.59 0.44 0.56 1.10
P6 0.43 0.17 0.83 1.03
P7 0.42 0.36 0.64 1.69
P8 0.46 0.31 0.69 1.21
P9 0.66 0.58 0.42 1.13
P10R 0.52 0.45 0.55 1.38
B1 0.66 0.49 0.51 1.03
B2 0.49 0.44 0.56 1.56
B3 0.57 0.49 0.51 1.28
B4 0.47 0.23 0.77 1.01
B5R 0.47 0.33 0.67 1.24
B6 0.55 0.49 0.51 1.36
B7 0.56 0.51 0.49 1.35
B8R 0.44 0.30 0.70 1.29
B9 0.76 0.60 0.40 1.00
B10 0.87 0.61 0.39 1.11
B11 0.87 0.61 0.39 1.12
B12 0.89 0.72 0.28 1.02
B13 0.73 0.57 0.43 1.01
B14R 0.66 0.63 0.37 1.21

2.3 Exploratory Factor Analysis (3 factors)

Fit indices of EFA
RMSEA TLI RMS CFI
0.07 0.9 0.04 0.92
EFA [3D] Summary
F1.loadings F2.loadings F3.loadings communality uniquenesses complexity
P1R 0.66 0.50 0.50 1.03
P2 0.6 0.57 0.43 1.30
P3R 0.5 0.27 0.73 1.11
P4 0.36 0.35 0.50 0.50 2.33
P5R 0.54 0.43 0.57 1.26
P6 0.42 0.22 0.78 1.36
P7 0.46 0.31 0.40 0.60 1.77
P8 0.48 0.33 0.67 1.30
P9 0.64 0.61 0.39 1.21
P10R 0.52 0.46 0.54 1.34
B1 0.85 0.71 0.29 1.03
B2 0.73 0.58 0.42 1.08
B3 0.78 0.66 0.34 1.02
B4 0.62 0.35 0.65 1.06
B5R 0.35 0.34 0.66 1.92
B6 0.53 0.52 0.48 1.48
B7 0.43 0.52 0.48 2.00
B8R 0.6 0.39 0.61 1.02
B9 0.62 0.60 0.40 1.19
B10 0.76 0.61 0.39 1.17
B11 0.86 0.64 0.36 1.07
B12 0.94 0.80 0.20 1.01
B13 0.68 0.59 0.41 1.05
B14R 0.55 0.64 0.36 1.52

2.4 Exploratory Factor Analysis (4 factors)

Fit indices of EFA
RMSEA TLI RMS CFI
0.06 0.92 0.03 0.95
EFA [4D] Summary
F1.loadings F2.loadings F3.loadings F4.loadings communality uniquenesses complexity
P1R 0.62 0.50 0.50 1.23
P2 0.52 0.63 0.37 1.56
P3R 0.65 0.35 0.65 1.06
P4 0.33 0.50 0.50 2.84
P5R 0.67 0.50 0.50 1.06
P6 0.35 0.24 0.76 2.52
P7 0.46 0.44 0.56 1.45
P8 0.42 0.37 0.63 1.42
P9 0.54 0.68 0.32 1.61
P10R 0.47 0.45 0.55 1.52
B1 0.81 0.70 0.30 1.07
B2 0.76 0.61 0.39 1.13
B3 0.82 0.70 0.30 1.06
B4 0.57 0.35 0.65 1.19
B5R 0.31 0.34 0.66 2.37
B6 0.44 0.55 0.45 1.86
B7 0.39 0.52 0.48 2.23
B8R 0.55 0.39 0.61 1.17
B9 0.49 0.59 0.41 1.63
B10 0.81 0.66 0.34 1.04
B11 0.79 0.65 0.35 1.04
B12 0.8 0.80 0.20 1.10
B13 0.63 0.61 0.39 1.17
B14R 0.54 0.34 0.68 0.32 1.76

2.5 Exploratory Graphical Analysis (500 bootstraps)

Contingency Table of Dimensionality Assessment for AW
Estimated Dimensions Frequency
3 33
4 43
5 18
6 6
Descriptives for Dimensionality Assessment for AW
n.Boots median.dim SD.dim SE.dim CI.dim Lower Upper
100 4 0.87 0.11 0.22 3.78 4.22

2.5.1 Number of times an item is estimated in the same factor/dimension as originaly estimated by EGA

2.6 CFA solution of Exploratory Graphical Analysis

##  [1] P2   P7   P8   P9   B6   B9   B10  B11  B12  B13  B14R
## 24 Levels: B1 B10 B11 B12 B13 B14R B2 B3 B4 B5R B6 B7 B8R B9 P10R ... P9
## [1] P6  B1  B2  B3  B4  B5R B7  B8R
## 24 Levels: B1 B10 B11 B12 B13 B14R B2 B3 B4 B5R B6 B7 B8R B9 P10R ... P9
## [1] P1R  P3R  P4   P5R  P10R
## 24 Levels: B1 B10 B11 B12 B13 B14R B2 B3 B4 B5R B6 B7 B8R B9 P10R ... P9

EGA fit measures of AW
chisq df pvalue cfi rmsea gfi nfi
252.11 249 0.43 1 0.01 0.99 0.98

2.7 CFA (1 factor)

Fit Measures
Fit Measures Value
1 npar 165.000
2 fmin 2.050
3 chisq 1619.577
4 df 252.000
5 pvalue 0.000
17 cfi 0.980
18 tli 0.979
19 nnfi 0.979
20 rfi 0.975
36 rmsea 0.117
48 rmr 0.070
50 srmr 0.072
51 srmr_bentler 0.070
59 gfi 0.982
60 agfi 0.970
61 pgfi 0.593
62 mfi 0.176

2.8 CFA (3 factors)

Fit Measures
Fit Measures Value
1 npar 168.000
2 fmin 1.131
3 chisq 893.748
4 df 249.000
5 pvalue 0.000
17 cfi 0.991
18 tli 0.990
19 nnfi 0.990
20 rfi 0.986
36 rmsea 0.081
48 rmr 0.056
50 srmr 0.058
51 srmr_bentler 0.056
59 gfi 0.990
60 agfi 0.983
61 pgfi 0.591
62 mfi 0.441

2.9 CFA (4 factors)

Fit Measures
Fit Measures Value
1 npar 171.000
2 fmin 0.927
3 chisq 732.361
4 df 246.000
5 pvalue 0.000
17 cfi 0.993
18 tli 0.992
19 nnfi 0.992
20 rfi 0.988
36 rmsea 0.071
48 rmr 0.051
50 srmr 0.053
51 srmr_bentler 0.051
59 gfi 0.992
60 agfi 0.986
61 pgfi 0.585
62 mfi 0.539









3. Dimensionality - as in the paper (i.e., using only the 19 items)

3.1. One-Factor

Fit Measures
Fit Measures Value
1 npar 125.000
2 fmin 0.932
3 chisq 736.105
4 df 135.000
5 pvalue 0.000
17 cfi 0.987
18 tli 0.985
19 nnfi 0.985
20 rfi 0.982
36 rmsea 0.106
48 rmr 0.062
50 srmr 0.065
51 srmr_bentler 0.062
59 gfi 0.988
60 agfi 0.977
61 pgfi 0.513
62 mfi 0.466

3.2. Two-Factor

Fit Measures
Fit Measures Value
1 npar 126.000
2 fmin 0.713
3 chisq 563.457
4 df 134.000
5 pvalue 0.000
17 cfi 0.991
18 tli 0.989
19 nnfi 0.989
20 rfi 0.986
36 rmsea 0.090
48 rmr 0.055
50 srmr 0.058
51 srmr_bentler 0.055
59 gfi 0.991
60 agfi 0.982
61 pgfi 0.511
62 mfi 0.580

3.3. Exploratory Graphical Analysis (500 bootstraps)

Contingency Table of Dimensionality Assessment for AW
Estimated Dimensions Frequency
2 1
3 36
4 42
5 15
6 5
7 1
Descriptives for Dimensionality Assessment for AW
n.Boots median.dim SD.dim SE.dim CI.dim Lower Upper
100 4 0.92 0.11 0.23 3.77 4.23









4. Exploring dimensionality - with Speciesism

Contingency Table of Dimensionality Assessment for AW
Estimated Dimensions Frequency
3 32
4 31
5 30
6 5
7 2
Descriptives for Dimensionality Assessment for AW
n.Boots median.dim SD.dim SE.dim CI.dim Lower Upper
100 4 1 0.12 0.25 3.75 4.25









5. Network Analysis