TABLE 2.
Monkey Da | Logit Transformation | ||||||||
Predictor | Sum of squares | df | Mean square | F | p | ||||
Cue discrimiminability | Discriminability | 1.2597 | 1 | 1.2597 | 9.25 | 0.000 | |||
High | Low | Identifiability | 42.9175 | 1 | 42.9175 | 315.26 | 0.003 | ||
Singleton identifiability | High | 78.3 ± 4.4 | 80.6 ± 4.2 | Discriminability x Identifiability | 0.1234 | 1 | 0.1234 | 91 | 0.343 |
Low | 51.2 ± 10.0 | 57.6 ± 11.4 | Error | 15.7915 | 116 | 0.1361 | |||
Monkey Le | Logit Transformation | ||||||||
Predictor | Sum of squares | df | Mean square | F | p | ||||
Cue discriminability | Discriminability | 0.009 | 1 | 556.1 | 0.04 | 0.850 | |||
High | Low | Identifiability | 209.5 | 1 | 0.04 | 843.65 | 0.000 | ||
Singleton identifiability | High | 87.2 ± 5.4 | 86.9 ± 5.6 | Discriminability x Identifiability | 0 | 1 | < 0.001 | < 0.001 | 0.968 |
Low | 35.1 ± 7.2 | 35.5 ± 10.0 | Error | 28.813 | 116 | 66.6 |