MBE

Author

Gibran Hemani

Published

July 12, 2017

Resources

Code (Language: R) Website Paper (Pub Date: 2017-07-12)

Other URLS: none

Method Contact: Fernando Hartwig ( fernandophartwig@gmail.com)

Entry Contact: Gibran Hemani ( g.hemani@bristol.ac.uk)

Context

Analysis Type: UVMR MVMR Network MR Bi-Directional MR Non-Linear

Input Data Types: Ind/Ind Ind/SS SS/Ind SS/SSfamily

Exposure Trait Types: Quantitative Binary Time to event

Outcome Trait Types: Quantitative Binary Time to event

Assumptions and Sources of Bias

Source of Bias Addressed
Weak instruments
Winner’s curse
Sample overlap
Uncorrelated horizontal pleiotropy
Correlated horizontal pleiotropy
Ancestry differences in samples
Residual confounding in GWAS
Cross-trait assortative mating
Index-event/conditioning on heritable trait

Description

The MBE is consistent when the largest number of similar (identical in infinite samples) individual-instrument causal effect estimates comes from valid instruments, even if the majority of instruments are invalid.