Structural Equation Modeling: What Is It For and Why Is It Useful for Genetics?

Abstract

The development of statistical methods for estimating genetic correlations from genome-wide association study (GWAS) summary statistics have produced ever-expanding “atlases” of genetic correlations among traits. As a... [ view full abstract ]

Authors

  1. K. Paige Harden (University of Texas at Austin)
  2. Andrew Grotzinger (University of Texas at Austin)
  3. Michel Nivard (Department of Biological Psychology, VU University)
  4. Elliot Tucker-Drob (University of Texas at Austin)

Topic Area

Statistical Methods

Session

SY-5A » Genomic Structural Equation Modeling Provides Insights into the Multivariate Genetic Architecture of Complex Traits (10:30 - Friday, 22nd June, Auditorium)

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