1 Introduction
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(1) How are users of prostheses and (2) different robots perceived in terms of the three major dimensions of social perception: Competence, Sociability, and Morality?
2 Social perception
2.1 Social perception of people wearing prostheses
2.2 Social perception of robots
3 Aims and research questions
4 Methods
4.1 Statistical analysis
5 Results
5.1 Missing values
5.2 Results: human stimuli
Predictors | Model 0 | Model 1 | Model 2 | ||||||
---|---|---|---|---|---|---|---|---|---|
b | SE | CI | b | SE | CI | b | SE | CI | |
(Intercept) | 3.88 | 0.03 | [3.82, 3.94] | 3.74 | 0.05 | [3.65, 3.82] | 4.25 | 0.21 | [3.82, 4.67] |
RF | 0.07 | 0.02 | [0.04, 0.10] | 0.07 | 0.02 | [0.04, 0.10] | |||
Gender | −0.16 | 0.06 | [−0.28, −0.04] | ||||||
Age | −0.01 | 0.00 | [−0.01, −0.00] | ||||||
Education | −0.01 | 0.03 | [−0.07, 0.05] | ||||||
Random Effetcs | |||||||||
σ2 | 0.18 | 0.18 | 0.18 | ||||||
τ00 | 0.27 id | 0.27 id | 0.26 id | ||||||
τ11 | |||||||||
ρ01 | |||||||||
ICC | 0.60 | 0.61 | 0.60 | ||||||
Model Fit | |||||||||
Marginal R2 | 0.000 | 0.008 | 0.034 | ||||||
Conditional R2 | 0.599 | 0.610 | 0.612 | ||||||
AIC | 1737.5 | 1726.5 | 1738.9 | ||||||
BIC | 1752.3 | 1746.2 | 1773.4 | ||||||
χ2 | 13.07** | 0.00 |
Predictors | Model 0 | Model 1 | Model 2 | ||||||
---|---|---|---|---|---|---|---|---|---|
b | SE | CI | b | SE | CI | b | SE | CI | |
(Intercept) | 3.86 | 0.03 | [3.27, 3.43] | 3.88 | 0.04 | [2.55, 3.74] | 4.36 | 0.18 | [4.02, 4.70] |
RF | −0.01 | 0.01 | [−0.07, 0.15] | −0.01 | 0.01 | [−0.03, 0.02] | |||
Gender | −0.15 | 0.05 | [−0.25, −0.05] | ||||||
Age | −0.00 | 0.00 | [−0.01, 0.00] | ||||||
Education | −0.02 | 0.02 | [−0.07, 0.02] | ||||||
Random Effects | |||||||||
σ2 | 0.10 | 0.10 | 0.10 | ||||||
τ00 | 0.19 id | 0.19 id | 0.18 id | ||||||
ICC | 0.65 | 0.65 | 0.64 | ||||||
Model Fit | |||||||||
Marginal R2 | 0.000 | 0.001 | 0.026 | ||||||
Conditional R2 | 0.646 | 0.646 | 0.648 | ||||||
AIC | 1229.8 | 1238.2 | 1252.4 | ||||||
BIC | 1244.5 | 1257.9 | 1286.8 | ||||||
χ2 | 0.00 | 0.00 |
Predictors | Model 0 | Model 1 | Model 2 | Model 3 | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
b | SE | CI | b | SE | CI | b | SE | CI | b | SE | CI | |
(Intercept) | 3.60 | 0.02 | [3.55, 3.64] | 3.76 | 0.03 | [3.70, 3.82] | 3.76 | 0.03 | [3.70, 3.82] | 4.13 | 0.16 | [3.81, 4.44] |
RF | −0.08 | 0.01 | [−0.10, −0.06] | −0.08 | 0.01 | [−0.10, −0.06] | −0.08 | 0.01 | [−0.10, −0.06] | |||
Gender | −0.06 | 0.04 | [−0.15, 0.03] | |||||||||
Age | −0.00 | 0.00 | [−0.01, 0.00] | |||||||||
Education | −0.04 | 0.02 | [−0.08, 0.01] | |||||||||
Random Effects | ||||||||||||
σ2 | 0.07 | 0.06 | 0.05 | 0.06 | ||||||||
τ00 | 0.16 id | 0.16 id | 0.19 id | 0.16 id | ||||||||
τ11 | 0.01 id.rf | |||||||||||
ρ01 | −0.38 id | |||||||||||
ICC | 0.69 | 0.71 | 0.77 | 0.71 | ||||||||
Model Fit | ||||||||||||
Marginal R2 | 0.000 | 0.020 | 0.020 | 0.032 | ||||||||
Conditional R2 | 0.690 | 0.719 | 0.772 | 0.721 | ||||||||
AIC | 900.38 | 842.44 | 832.00 | 863.45 | ||||||||
BIC | 915.14 | 862.12 | 861.53 | 897.90 | ||||||||
χ2 | 59.94** | 14.44** | 0.00 |
5.3 Results: robotic stimuli
Predictors | Model 0 | Model 1 | Model 2 | Model 3 | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
b | SE | CI | b | SE | CI | b | SE | CI | b | SE | CI | |
(Intercept) | 3.77 | 0.04 | [3.69, 3.86] | 6.31 | 0.22 | [5.89, 6.73] | 6.32 | 0.23 | [5.87, 6.77] | 7.29 | 0.34 | [6.61, 7.96] |
GOT | −0.51 | 0.04 | [−0.59, −0.42] | −0.51 | 0.04 | [−0.60, −0.42] | −0.51 | 0.04 | [−0.59, −0.42] | |||
Gender | −0.33 | 0.08 | [−0.48, −0.18] | |||||||||
Age | −0.01 | 0.00 | [−0.02, −0.01] | |||||||||
Education | −0.01 | 0.04 | [−0.09, 0.07] | |||||||||
Random Effects | ||||||||||||
σ2 | 1.14 | 0.91 | 0.81 | 0.91 | ||||||||
τ00 | 0.12 id | 0.19 id | 3.09 id | 0.15 id | ||||||||
τ11 | 0.11 id.got | |||||||||||
ρ01 | −0.96 id | |||||||||||
ICC | 0.10 | 0.17 | 0.26 | 0.14 | ||||||||
Model Fit | ||||||||||||
Marginal R2 | 0.000 | 0.131 | 0.132 | 0.166 | ||||||||
Conditional R2 | 0.098 | 0.278 | 0.358 | 0.286 | ||||||||
AIC | 2509.5 | 2385.7 | 2386.0 | 2382.0 | ||||||||
BIC | 2523.6 | 2404.5 | 2414.2 | 2414.9 | ||||||||
χ2 | 125.83** | 3.70 | 6.04* |
Predictors | Model 0 | Model 1 | Model 2 | ||||||
---|---|---|---|---|---|---|---|---|---|
b | SE | CI | b | SE | CI | b | SE | CI | |
(Intercept) | 3.35 | 0.04 | [3.27, 3.43] | 3.25 | 0.14 | [2.53, 3.72] | 3.38 | 0.31 | [2.43, 4.06] |
GOT | 0.04 | 0.06 | [−0.07, 0.15] | 0.04 | 0.06 | [−0.07, 0.15] | |||
Gender | −0.07 | 0.08 | [−0.23, 0.09] | ||||||
Age | 0.01 | 0.00 | [−0.00, 0.01] | ||||||
Education | −0.04 | 0.04 | [−0.12, 0.04] | ||||||
Random Effects | |||||||||
σ2 | 0.34 | 0.34 | 0.34 | ||||||
τ00 | 0.11 id | 0.11 id | 0.11 id | ||||||
ICC | 0.25 | 0.25 | 0.25 | ||||||
Model Fit | |||||||||
Marginal R2 | 0.000 | 0.001 | 0.012 | ||||||
Conditional R2 | 0.251 | 0.249 | 0.258 | ||||||
AIC | 686.45 | 691.87 | 711.73 | ||||||
BIC | 697.88 | 707.12 | 738.41 | ||||||
χ2 | 0.00 | 0.00 |
Predictors | Model 0 | Model 1 | Model 2 | ||||||
---|---|---|---|---|---|---|---|---|---|
b | SE | CI | b | SE | CI | b | SE | CI | |
(Intercept) | 3.40 | 0.06 | [3.27, 3.52] | 3.69 | 0.15 | [3.45, 4.65] | 3.38 | 0.49 | [2.63, 4.83] |
GOT | −0.12 | 0.05 | [−0.22, −0.01] | −0.12 | 0.05 | [−0.22, −0.01] | |||
Gender | 0.05 | 0.14 | [−0.22, 0.32] | ||||||
Age | 0.00 | 0.01 | [−0.01, 0.02] | ||||||
Education | 0.02 | 0.06 | [−0.11, 0.14] | ||||||
Random Effects | |||||||||
σ2 | 0.14 | 0.13 | 0.13 | ||||||
τ00 | 0.29 id | 0.30 id | 0.31 id | ||||||
ICC | 0.68 | 0.70 | 0.71 | ||||||
Model Fit | |||||||||
Marginal R2 | 0.000 | 0.015 | 0.021 | ||||||
Conditional R2 | 0.679 | 0.702 | 0.712 | ||||||
AIC | 266.43 | 267.78 | 286.84 | ||||||
BIC | 275.38 | 279.72 | 307.73 | ||||||
χ2 | 0.64 | 0.00 |