MR Dictionary

MR accounting for Correlated and Idiosyncratic Pleiotropy (MRCIP)

A two-sample MR method that aims to account for pleiotropic instrumental variables (IVs) that may lead to a biased causal effect estimate (i.e., unbalanced horizontal pleiotropy).

The method relies on a random-effects model that accounts for correlated pleiotropy, where the effects of the IV on the exposure and outcome (not mediated by the exposure) are considered as random effects with possible correlation between them. To handle the presence of idiosyncratic pleiotropy, the model includes novel weights informed by transformed Pearson residuals, which down-weight pleiotropic IVs. For estimation of the causal effect, model parameters are estimated by maximizing a weighted likelihood function with an algorithm (called "PRW-EM"), which combines an expectation-maximization algorithm with an iterative mechanism for updating the weights. Unlike many MR methods, MRCIP provides valid causal inference even if the INstrument Strength Independent of Direct Effect (InSIDE) assumption is violated and it does not require the presence of valid IVs.


Other terms in 'Pleiotropy-robust two-sample MR methods':