Table 4.

Estimated coefficients, standard errors and p-values

SNP	marginal	s.e.	conditional	s.e.	“true”
rs10852521	−0.027	0.0055	−0.171	0.0047	−0.168
rs11075985	0.093	0.0051	0.134	0.0040	0.118
rs11075987	−0.019	0.0055	−0.163	0.0031	−0.192
rs11075989	0.057	0.0054	−0.043	0.0035	−0.050
rs11642841	0.070	0.0053	0.026	0.0029	0.006
rs12149832	0.084	0.0052	0.085	0.0032	0.068
rs8057044	0.106	0.0050	0.278	0.0031	0.304
rs9922619	0.042	0.0055	−0.092	0.0033	−0.076

The marginal models are BMI~SNP_i. The conditional model is BMI~HIP + WC + SNP₁ + SNP₂ + ⋯ + SNP₈. The true model was generated using the original GWAS data. The covariance for SNPs was estimated from the 381 European subjects from the 1000 Genomes Project data (The 1000 Genomes Project Consortium 2015). When building the conditional model for simulated data, we multiplied non-diagonal elements of the variance-covariance matrix by 0.8, since the same adjustment was made to generate these data. 2000 independent null SNPs with MAF f~U [0.1, 0.5] were simulated to estimate the correlation between traits. λ = 0.01.