Causal Inference Methods to Integrate Omics and Complex Traits

Matching Methods for Causal Inference

Causal inference in studies and medical articles

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Identification of causal genes for complex traits

MOTIVATION Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider 'causal variants' as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the...

Doubly Robust Causal Inference With Complex Parameters

Semiparametric doubly robust methods for causal inference help protect against bias due to model misspecification, while also reducing sensitivity to the curse of dimensionality (e.g., when high-dimensional covariate adjustment is necessary). However, doubly robust methods have not yet been developed in numerous important settings. In particular, standard semiparametric theory mostly only consi...

Causal inference methods to study nonrandomized, preexisting development interventions.

Empirical measurement of interventions to address significant global health and development problems is necessary to ensure that resources are applied appropriately. Such intervention programs are often deployed at the group or community level. The gold standard design to measure the effectiveness of community-level interventions is the community-randomized trial, but the conditions of these tr...