IV & MR (project page)
Publications
Causal mediation analysis for time-varying heritable risk factors with Mendelian Randomization
A new Bayesian full-information method for life-course Mendelian randomization
Almost exact Mendelian randomization
By combining causal graphs and randomization inference, a formal justification for Mendelian randomization is given in the context of with-family studies.
Mendelian randomization
Mendelian randomization (MR) is a term that applies to the use of genetic variation to address causal questions about how modifiable …
Mendelian randomization with coarsened exposures
A key assumption in Mendelian randomisation is that the relationship between the genetic instruments and the outcome is fully mediated …
A latent mixture model for heterogeneous causal mechanisms in Mendelian randomization
There is a general lack of awareness that MR can be used to discover multiple biological mechanisms, partly due to the wide usage of the broad terminology ’effect heterogeneity’ to refer to several different phenomena. This article introduces the concept of mechanistic heterogeneity and proposes a latent mixture model to make inference about the causal mechanisms.
Causal inference for heritable phenotypic risk factors using heterogeneous genetic instruments
We greatly improve the applicability of MR-RAPS. The new GRAPPLE framework can handle multiple exposures and overlapping exposure and …
ivmodel: An R package for inference and sensitivity analysis of instrumental variables models with one endogenous variable
Vignette of an R package for instrumental variable regression.
Profile-likelihood Bayesian model averaging for two-sample summary data Mendelian randomization in the presence of horizontal pleiotropy
We propose a Bayesian model averaging method to account for the uncertainty about instrument validity in Mendelian randomization. This model is extended to allow for a large fraction of SNPs violating the InSIDE assumption.
A Mendelian randomization study of the role of lipoprotein subfractions in coronary artery disease
We apply the MR-RAPS method we developed in previous articles to infer the potential causal role of lipoprotein subfractions in CAD. This is motivated by the finding in our earlier IJE paper that the association between genetically-determined HDL-C and CAD is heterogeneous according to instrument strength. In this study, We find that HDL subfraction traits, unlike LDL and VLDL subfractions, appear to have heterogeneous effects on coronary artery disease according to particle size. The concentration of medium HDL particles may have a protective effect on CAD that is independent of traditional lipid factors.
Falsification tests for instrumental variable designs with an application to tendency to operate
We propose a falsification test for the IV assumptions using sub-populations of the data with overwhelming proportion of treated or …
Graphical diagnosis of confounding bias in instrumental variables analysis
This research letter proposes a new diagnostic plot for IV analysis, so large bias ratios (compared to OLS estimator) are not …
Powerful three-sample genome-wide design and robust statistical inference in summary-data Mendelian randomization
We extend the MR-RAPS method in our previous paper using the empirical partially Bayes framework described by Lindsay, allowing a true …
Improving the accuracy of two-sample summary data Mendelian randomization: moving beyond the NOME assumption
This paper proposes a modified Cochran’s $Q$ statistic to detect horizontal pleiotropy in Mendelian randomization. This extension …
Statistical inference in two-sample summary-data Mendelian randomization using robust adjusted profile score
We provide a comprehensive theoretical basis for two-sample summary-data Mendelian randomization. We find that horizontal pleiotropy is …
Two-sample instrumental variable analyses using heterogeneous samples
Many modern IV studies (especially Mendelian Randomization) are carried out with the two-sample design, where the samples may come from …
Talks
Almost exact Mendelian randomization
By combining causal graphs and randomization inference, a formal justification for Mendelian randomization is given in the context of with-family studies.
The randomization principle in causal inference: A modern look at some old ideas
Randomization is a fundamental principle in causal inference and was first proposed by R A Fisher about a century ago. Although …
Mendelian randomization: Old and new insights
Mendelian randomization (MR) is a method for causal inference that utilizes the natural experiment in genetic inheritance. The idea of …
Mendelian randomization: Old and new insights
Mendelian randomization (MR) is a method for causal inference that utilizes the natural experiment in genetic inheritance. The idea of …
Discovering mechanistic heterogeneity using Mendelian randomization
Mendelian Randomization (MR) is a popular method in epidemiology and genetics that uses genetic variation as instrumental variables for …
MR Data Challenge 2019
This report entered the 2019 MR Data Challenge and contains reproducible R code for our analysis.
The statistics of summary-data Mendelian randomization
Invited talk giving an overview of my research on summary-data Mendelian randomization.
Mendelian randomization: A tutorial
Tutorial talk for the theory, methods, and practice of Mendelian randomization.