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.