Table 2.
Parameter Estimates (±Unconditional Standard Error) for Models of the Genetic Architecture of Cannabinoid Inheritance: Cannabidiol
| Model |
AICC weight (wi) |
Estimate (SE) |
||
|---|---|---|---|---|
| (1) de Meijer et al.2 | Ca | Aa | AaAa | |
| Ca | 0.558 | 1.40 (0.07) | ||
| Aa | 0.374 | 2.77 (0.16) | ||
| AaAa | 0.040 | −2.79 (0.29) | ||
| Variable importance -> | 0.560 | 0.391 | 0.040 | |
| Model |
AICC weight (wi) |
Estimate (SE) |
|||
|---|---|---|---|---|---|
| (2) Staginnus et al.29 | Aa | Ca | Ad | Mea | |
| Aa |
0.817 |
48.79 (3.67) |
|
|
|
| Ca |
0.075 |
|
28.63 (3.96) |
|
|
| Aa, Ad |
0.043 |
42.95 (1.98) |
|
11.37 (1.98) |
|
| Mea |
0.026 |
|
|
|
31.63 (5.77) |
| Variable importance -> | 0.884 | 0.098 | 0.044 | 0.027 | |
Cannabinoid inheritance is described for CBD based on data from either (1) de Meijer et al.2 or (2) Staginnus et al.29 and an assessment of variable importance within the model and the Akaike weight associated with each genetic effect. AIC corrected for finite sample size (AICC) weights were used to select the models for presentation when the minimum number of models whose weights sum to >95%.