Article

A latent outcome variable approach for Mendelian randomization using the expectation maximization algorithm

2024-08-26

Abstract excerpt

Mendelian randomization (MR) is a widely used tool to uncover causal relationships between exposures and outcomes. However, existing MR methods can suffer from inflated type I error rates and biased causal effects in the presence of invalid instruments. Our proposed method enhances MR analysis by augmenting latent phenotypes of the outcome, explicitly disentangling horizontal and vertical pleiotropy effects. This...

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Literature Corpus work: 84928dd3-3fcb-5e85-b575-a7bd41a31afb
DOI: 10.1101/2024.08.24.24312485

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