Table 2. Model selection results using the information theoretic approach1.
| Predicting Leucocytozoon infection | |||||||
| Model | AICc | ΔAICc | AICc Weights | Model Likelihood | Parameters | Deviance | R-squared |
| {ψ area, ρ hematozoa prevalence} | 436.4206 | 0 | 0.82122 | 1 | 4 | 428.2882 | |
| {ψ wind, ρ hematozoa prevalence} | 439.4699 | 3.0493 | 0.17878 | 0.2177 | 3 | 433.3907 | 0.949981718 |
| {ψ migration duration, ρ hematozoa prevalence} | 500.5873 | 64.1667 | 0 | 0 | 3 | 494.5081 | 0.350866118 |
| {ψ migration distance, ρ hematozoa prevalence} | 504.4218 | 68.0012 | 0 | 0 | 3 | 498.3426 | 0.313277661 |
| {ψ temperature, ρ hematozoa prevalence} | 516.8494 | 80.4288 | 0 | 0 | 3 | 510.7702 | 0.191453613 |
| {ψ, ρ hematozoa prevalence} | 534.3404 | 97.9198 | 0 | 0 | 2 | 530.3009 | |
| Predicting Haemoproteus / Parahaemoproteus / Plasmodium infection | |||||||
| Model | AICc | ΔAICc | AICc Weights | Model Likelihood | Parameters | Deviance | R-squared |
| {ψ area, ρ hematozoa prevalence} | 277.4747 | 0 | 0.95578 | 1 | 4 | 269.3423 | |
| {ψ wind, ρ hematozoa prevalence} | 283.6705 | 6.1958 | 0.04315 | 0.0451 | 3 | 277.5913 | 0.938686787 |
| {ψ temperature, ρ hematozoa prevalence} | 291.0593 | 13.5846 | 0.00107 | 0.0011 | 3 | 284.9801 | 0.883767273 |
| {ψ migration duration, ρ hematozoa prevalence} | 405.5536 | 128.0789 | 0 | 0 | 3 | 399.4744 | 0.032753401 |
| {ψ migration distance, ρ hematozoa prevalence} | 407.21 | 129.7353 | 0 | 0 | 3 | 401.1308 | 0.020441702 |
| {ψ, ρ hematozoa prevalence} | 407.9204 | 130.4457 | 0 | 0 | 2 | 403.881 | |
1
Unresolved samples considered as negative for infection.