Logistic regression models to predict whether participants made a reduction cut at the correct angle rather than too shallow (leaving a stub) from independent variables (type of training, participant’s previous experience with plants). Models were based on pooled data from 3 cities. Model parameters include the number of predictors (K), Akaike’s Information Criterion corrected for small sample sizes (AICc), comparison of model AICc with AICc of the best model (ΔAICc), goodness of fit (ModelLik), and log likelihood (LL).
| Model | K | AICc | ΔAICc | ModelLik | LL |
|---|---|---|---|---|---|
| Training | 2 | 28.71 | 0.00 | 1.00 | −12.22 |
| Intercept only (null) | 1 | 37.71 | 9.00 | 0.01 | −17.81 |
| Experience | 5 | 37.97 | 9.25 | 0.01 | −13.23 |