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Activity Number: 88 - SPEED: Causal Inference and Related Methodology Part 2
Type: Contributed
Date/Time: Sunday, July 28, 2019 : 5:05 PM to 5:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #307509
Title: Testing for Weak Instruments in Two Sample Summary Data Multivariable Mendelian Randomisation
Author(s): Eleanor Sanderson* and Jack Bowden
Companies: University of Bristol and University of Bristol
Keywords: Mendelian Randomisation; F-test; Weak Instruments; Instrumental Variables

Multivariable Mendelian randomisation (MVMR) is a form of instrumental variable estimation which utilises genetic variants to estimate the direct causal effects of multiple exposures on an outcome. A key assumption required for consistent MVMR estimation is that the genetic variants used as instruments can strongly predict each exposures. For MVMR this means that the genetic variants must be able to predict each exposure conditional on having predicted all of the other exposures included in the model. In analysis using individual level data this assumption can be tested using a conditional F-statistic. We consider how to define weak instruments in the two-sample summary data MVMR setting and show that a summary data F-statistic, calculated from an adjusted Q statistic could be used to test for weak instruments. We show that this summary data F-statistic has the same distribution as the individual level conditional F-statistic but that it depends on data that is generally not reported in standard summary statistics. We use simulations to explore how sensitive this summary data F-statistic is to the missing data and explore strategies for estimation when this data is not available.

Authors who are presenting talks have a * after their name.

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