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Chunk #20 — Results — SNP Effects — Performance in Empirical Data under Controlled Missingness.

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Genomic structural equation modelling provides insights into the multivariate genetic architecture of complex traits.
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mean χ2 values) were for Genomic SEM of the individual neuroticism items presented above, indicating that construction of composite indices via averaging, though convenient, removes multivariate information that can otherwise be retained with Genomic SEM (Supplementary Table 8). Genomic SEM analyses that incorporated supplemental information from parcels containing imposed missing data consistently outperformed GWAS of individual parcels with complete data, and performed nearly as well as analyses of complete data across all three parcels. Thus, inclusion of summary data from genetically correlated, phenotypes in Genomic SEM may boost power relative GWAS of the individual phenotypes, even when there is high sample overlap and sample sizes are uneven across phenotypes.