Table 1 Causal effects estimated from 200 simulated datasets for each configuration from two MR methods (Bayesian, IVW) when β₁=β₂=0.3, using four metrics: mean, standard deviation (sd), coverage and power. The six configurations were generated from three missing rates of the exposures (80%, 50%, 20%) and two levels of IV strength (α=0.3 and 0.1). \(\hat {\beta }_{1}\): estimated causal effect of X₁ on \(Y_{1}, \hat {\beta }_{2}\): estimated causal effect of X₂ on Y₂

From: Bayesian mendelian randomization with study heterogeneity and data partitioning for large studies