principal component eigenvalues for population stratification adjustments (10 components for ARIC and statistically significant components for FHS). Models were implemented using ProbABEL71 in ARIC, R72 in CHS, linear mixed effects models with fixed effects for SNPs and random effects for individuals correlated within families73 in FHS, and MACH2QTL65 in RS as implemented in GRIMP74. In FHS, the kinship package in R generated a covariance matrix for each family based on the kinship coefficient for each relative pair. The kinship matrix, which includes the full set of family-specific covariance matrices, specified the covariance matrix for the random effects.
