Table 1:
Gender | BMIa | N | τ 1 | π0 b | π 1 | Prπ1 | λ0 b | λ1 b | λ 2 | Prλ2 | PrξE | PrξG |
---|---|---|---|---|---|---|---|---|---|---|---|---|
| ||||||||||||
All | Std | 11586 | 0.19 | 0.25 | 0.06 | 1.78e-11 | 0.93 | 0.12 | 0.09 | 7.49e-50 | 1.76e-02 | 7.89e-04 |
All | BC | 11586 | 0.17 | 0.26 | 0.04 | 1.79e-05 | 0.95 | 0.06 | 0.02 | 1.15e-03 | 2.68e-02 | 5.14e-04 |
All | BN | 11586 | 0.17 | 0.26 | 0.04 | 2.52e-05 | 0.95 | 0.06 | 0.02 | 1.14e-03 | 2.66e-02 | 6.56e-04 |
All | Res | 11586 | 0.20 | 0.26 | 0.06 | 3.99e-12 | 0.93 | 0.11 | 0.09 | 1.01e-53 | 9.37e-03 | 5.28e-04 |
| ||||||||||||
M | Std | 5022 | 0.19 | 0.26 | 0.04 | 4.69e-04 | 0.93 | 0.12 | 0.09 | 1.63e-22 | 3.91e-01 | 2.75e-01 |
M | BC | 5022 | 0.17 | 0.26 | 0.03 | 2.11e-02 | 0.95 | 0.07 | 0.03 | 1.33e-03 | 3.83e-01 | 1.65e-01 |
M | BN | 5022 | 0.17 | 0.26 | 0.03 | 3.05e-02 | 0.95 | 0.06 | 0.03 | 4.84e-03 | 3.86e-01 | 1.78e-01 |
M | Res | 5022 | 0.19 | 0.26 | 0.04 | 4.54e-04 | 0.93 | 0.11 | 0.08 | 4.70e-22 | 3.99e-01 | 2.04e-01 |
| ||||||||||||
F | Std | 6564 | 0.20 | 0.25 | 0.06 | 6.65e-09 | 0.93 | 0.12 | 0.09 | 3.51e-31 | 2.24e-02 | 1.21e-03 |
F | BC | 6564 | 0.18 | 0.26 | 0.04 | 2.09e-04 | 0.94 | 0.06 | 0.02 | 1.11e-02 | 3.82e-02 | 1.75e-03 |
F | BN | 6564 | 0.18 | 0.26 | 0.04 | 2.10e-04 | 0.94 | 0.06 | 0.02 | 6.43e-03 | 3.66e-02 | 1.95e-03 |
F | Res | 6564 | 0.20 | 0.26 | 0.07 | 1.46e-09 | 0.92 | 0.12 | 0.09 | 7.91e-33 | 1.06e-02 | 8.36e-04 |
We consider four transformations of BMI. Std denotes the standardized mean BMI shown in the middle panel of Figure E.1. BC denotes the Box-Cox transformation [29]. BN denotes the transformation from bestNormalize [30]. Res denotes analysis of standardized variables after all (BMI, birthyear, PGS) have been residualized on 10 PCs and gender as per Frisch–Waugh–Lovell theorem given previous concerns regarding interaction research [5].
We show probabilities for parameters when the maximal probability in a column is larger than 1e − 6.