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. 2020 Jan 7;11:29. doi: 10.1038/s41467-019-13870-3

Table 1.

Mean squared error (MSE) of the causal effect estimates from the competing methods on the NMR metabolite and blood cell trait data.

Setting A Setting B
R2: 0.1 0.3 0.5 0.1 0.3 0.5
Scenario 1:
IVW 0.6727 0.1675 0.0784 0.5949 0.1619 0.0629
Lars 0.1292 0.0447 0.0298 0.1559 0.0648 0.0372
Lasso 0.0604 0.0289 0.0162 0.1046 0.0503 0.0307
Elastic Net 0.0673 0.0300 0.0162 0.1161 0.0480 0.0287
MR-BMA 0.0340 0.0175 0.0105 0.0534 0.0368 0.0306
Best model 0.0717 0.0320 0.0156 0.0921 0.0514 0.0376
Scenario 2:
IVW 22.9516 6.0594 2.6257 23.2495 5.7715 2.4802
Lars 0.0354 0.0367 0.0094 0.0321 0.0212 0.0143
Lasso 0.0064 0.0047 0.0039 0.0105 0.0086 0.0074
Elastic Net 0.0064 0.0044 0.0034 0.0098 0.0078 0.0067
MR-BMA 0.0051 0.0039 0.0032 0.0088 0.0076 0.0063
Best model 0.0114 0.0081 0.0061 0.0150 0.0121 0.0096
Scenario 3:
IVW 1.6200 0.4272 0.1742 2.3140 0.6208 0.2566
Lars 0.3461 0.1151 0.0482 0.5892 0.1669 0.0844
Lasso 0.0161 0.0067 0.0040 0.0378 0.0225 0.0166
Elastic Net 0.0168 0.0074 0.0044 0.0451 0.0224 0.0169
BMA 0.0066 0.0034 0.0019 0.0235 0.0165 0.0149
Best model 0.0128 0.0051 0.0027 0.0444 0.0242 0.0177

We mark in bold font the lowest MSE in each experimental setting. Scenario 1: NMR metabolites, d = 12 risk factors, Scenario 2: NMR metabolites, d = 92 risk factors, and Scenario 3: blood cell traits, d = 33 risk factors. Setting A includes four true causal risk factors which increase the risk and Setting B includes eight true causal risk factors of which half are protective and the other half increases the risk