Table 2

Genetic correlation results

Between-Trait Correlations
Trait 1Trait 2RgSE
Levels 
 BMI Education –.3576 .0304 
 BMI Height –.1824 .0262 
 BMI NEB .1657 .0466 
 Education Height .2708 .0280 
 Education NEB –.2850 .0530 
 Height NEB –.1048 .0407 
Squared z Score 
 BMI Education –.1129 .1138 
 BMI Height .0928 .1887 
 BMI NEB .3697 .2395 
 Education Height .3161 .3503 
 Education NEB –.1571 .3193 
 Height NEB .0948 .5428 
  Within-Trait Correlations
With HLMM Additive
TraitvPGSRgSE
BMI Levene's –.4867 .09744 
BMI Sibling standard deviation Not identified Not identified 
BMI Squared z –.9004 .04162 
Education Levene's −1.0709 .0390 
Education Sibling standard deviation .2832 .2552 
Education Squared z –.8291 .1019 
Height Levene's –.05683 .283 
Height Sibling standard deviation Not identified Not identified 
Height Squared z –.8894 .3587 
NEB Levene's .5181 .0913 
NEB Sibling standard deviation .0989 .2876 
NEB Squared z –.0951 .1515 
Between-Trait Correlations
Trait 1Trait 2RgSE
Levels 
 BMI Education –.3576 .0304 
 BMI Height –.1824 .0262 
 BMI NEB .1657 .0466 
 Education Height .2708 .0280 
 Education NEB –.2850 .0530 
 Height NEB –.1048 .0407 
Squared z Score 
 BMI Education –.1129 .1138 
 BMI Height .0928 .1887 
 BMI NEB .3697 .2395 
 Education Height .3161 .3503 
 Education NEB –.1571 .3193 
 Height NEB .0948 .5428 
  Within-Trait Correlations
With HLMM Additive
TraitvPGSRgSE
BMI Levene's –.4867 .09744 
BMI Sibling standard deviation Not identified Not identified 
BMI Squared z –.9004 .04162 
Education Levene's −1.0709 .0390 
Education Sibling standard deviation .2832 .2552 
Education Squared z –.8291 .1019 
Height Levene's –.05683 .283 
Height Sibling standard deviation Not identified Not identified 
Height Squared z –.8894 .3587 
NEB Levene's .5181 .0913 
NEB Sibling standard deviation .0989 .2876 
NEB Squared z –.0951 .1515 

Notes: NEB = the number of children ever born. The top panel shows the between-trait correlation in the standard levels weights and the between-trait correlation in the squared z vPGS weights, which are generally better powered. The bottom panel shows the within-trait correlation between (1) the additive weights produced by the HLMM method, which are meant to identify mean effects purged of mean–variance correlations; and (2) the non-HLMM vPGS.

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