Table 2.
Results of mixed-effects logistic regression for predicting the likelihood of correctly recognizing an item image (hit)
| Dependent variable: correctly recognizing an old item image (hit) | ||||||
|---|---|---|---|---|---|---|
| Model 1 | Model 2 | |||||
| Odds ratio | CI | P | Odds ratios | CI | P | |
| Fixed effects | ||||||
| Intercept | 4.07 | 3.03–5.45 | <0.001 | 2.96 | 1.93–4.53 | <0.001 |
| Valence: neutral | 0.73 | 0.58–0.92 | 0.007 | 0.86 | 0.65–1.14 | 0.288 |
| Valence: positive | 0.92 | 0.72–1.18 | 0.509 | 0.98 | 0.76–1.26 | 0.875 |
| Rated arousal | 1.10 | 1.00–1.20 | 0.046 | |||
| Random effects | ||||||
| σ2 | 3.29 | 3.29 | ||||
| n | 42 | 42 | ||||
-
Model 1 included the predictor context valence. Model 2 additionally included the predictor-rated arousal. Model 2 significantly reduced residual deviance compared to model 1. Bold indicates statistical significance of predictors (for a better overview).
