Models | np | Deviance | AICc | ΔAICc | w i |
---|---|---|---|---|---|
Hypothesis 1 | |||||
logit(dexp) = age | 4 | 310.25 | 318.4 | 0.00 | 0.38 |
logit(dexp) = age + sex | 5 | 309.36 | 319.6 | 1.18 | 0.21 |
logit(dexp) = age + disp | 5 | 310.11 | 320.3 | 1.94 | 0.15 |
logit(dexp) = (.) | 2 | 317.77 | 321.8 | 3.43 | 0.07 |
logit(dexp) = sex | 3 | 316.46 | 322.5 | 4.16 | 0.05 |
logit(dexp) = age + sex*disp | 7 | 308.65 | 323.0 | 4.65 | 0.04 |
logit(dexp) = age*sex | 7 | 308.78 | 323.2 | 4.78 | 0.03 |
logit(dexp) = disp | 3 | 317.74 | 323.8 | 5.44 | 0.03 |
logit(dexp) = sex + disp | 4 | 316.25 | 324.4 | 6.00 | 0.02 |
logit(dexp) = age*sex + disp | 8 | 308.35 | 324.8 | 6.46 | 0.02 |
logit(dexp) = sex*disp | 5 | 316.15 | 326.4 | 7.97 | 0.01 |
logit(dexp) = age*sex + sex*disp | 11 | 308.15 | 326.8 | 8.39 | 0.00 |
Hypothesis 2 | |||||
logit(dexp) = age + per | 6 | 294.25 | 306.5 | 0.00 | 0.33 |
logit(dexp) = age + per*disp | 9 | 288.77 | 307.4 | 0.85 | 0.21 |
logit(dexp) = age + sex + per | 7 | 293.52 | 307.9 | 1.37 | 0.17 |
logit(dexp) = age + disp + per | 7 | 293.84 | 308.2 | 1.69 | 0.14 |
logit(dexp) = per | 4 | 300.36 | 308.5 | 1.96 | 0.12 |
logit(dexp) = age + sex*per | 9 | 293.00 | 311.6 | 5.08 | 0.03 |
logit(dexp) = age | 4 | 310.25 | 318.4 | 11.84 | 0.00 |
logit(dexp) = age + sex | 5 | 309.36 | 319.6 | 13.02 | 0.00 |
logit(dexp) = age + disp | 5 | 310.11 | 320.3 | 13.78 | 0.00 |