Table 2.
Parameter | Odds ratio | SE | Z | P | 95% bounds
|
|
---|---|---|---|---|---|---|
Upper | Lower | |||||
Model 1* | ||||||
Gesture | 1.04 | 0.42 | 0.09 | 0.925 | 0.47 | 2.32 |
Trial | 0.91 | 0.02 | −5.25 | <0.001 | 0.88 | 0.95 |
Position | 1.56 | 0.63 | 1.10 | 0.271 | 0.71 | 3.42 |
Brandy | 4.57 | 4.32 | 1.61 | 0.108 | 0.72 | 29.12 |
Candy | 0.48 | 0.35 | −1.02 | 0.308 | 0.12 | 1.97 |
Jadine | 1.32 | 1.02 | 0.36 | 0.718 | 0.29 | 5.97 |
Kara | 0.20 | 0.14 | −2.25 | 0.025 | .05 | 0.81 |
Megan | 0.12 | 0.09 | −2.81 | 0.005 | 0.29 | 0.53 |
Mindy | 0.09 | 0.07 | −3.15 | 0.002 | 0.02 | 0.41 |
Model 2† | ||||||
Gesture | 0.82 | 0.20 | −0.79 | 0.427 | 0.51 | 1.32 |
Trial | 0.93 | 0.02 | −3.48 | <0.001 | 0.90 | 0.97 |
Position | 1.41 | 0.32 | 1.53 | −0.127 | 0.91 | 2.19 |
The binary logistic regression model included categorical variables for individuals as predictors in addition to the variables shown. The variable gesture was coded so that the odds ratios would exceed 1 if actors were more likely to dislodge the other reward when a recipient gestured.
The binary logistic regression model used clustered robust standard errors to calculate the confidence intervals for predictor variables.