Article

A novel and efficient machine learning Mendelian randomization estimator applied to predict the safety and efficacy of sclerostin inhibition

2024-01-31

Abstract excerpt

1 Mendelian Randomization (MR) enables estimation of causal effects while controlling for unmeasured confounding factors. However, traditional MR’s reliance on strong parametric assumptions can introduce bias if these are violated. We introduce a new machine learning MR estimator named Quantile Instrumental Variable (IV) that achieves low estimation error in a wide range of plausible MR scenarios. Quantile IV is d...

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Literature Corpus work: 38862b26-649f-516d-99c1-83dba4962688
DOI: 10.1101/2024.01.30.24302021

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