16 citations · 19 across the 9 of their papers we have counts for
10 papers
Multivariable Mendelian randomization with weak instruments: a comparison of Bayesian and frequentist methods
Andrew J. Grant, Ashish Patel, Stephen Burgess
Weak instruments are a well known limitation for valid causal inference in Mendelian randomization studies. In the single exposure setting, weak instrument bias can be mitigated by…
Efficient semiparametric estimation of marginal treatment effects with genetic instrumental variables
Ashish Patel, Francis J DiTraglia, Stephen Burgess
Alcohol misuse is a key target of public health strategies aimed at reducing cardiovascular risk. The effect of excessive alcohol consumption on blood pressure may vary systematica…
Stratification-based Instrumental Variable Analysis Framework for Nonlinear Effect Analysis
Haodong Tian, Ashish Patel, Stephen Burgess
Nonlinear causal effects are prevalent in many research scenarios involving continuous exposures, and instrumental variables (IVs) can be employed to investigate such effects, part…
Weak instruments in multivariable Mendelian randomization: methods and practice
Ashish Patel, James Lane, Stephen Burgess
The method of multivariable Mendelian randomization uses genetic variants to instrument multiple exposures, to estimate the effect that a given exposure has on an outcome condition…
Estimating time-varying exposure effects through continuous-time modelling in Mendelian randomization
Haodong Tian, Ashish Patel, Stephen Burgess
Mendelian randomization is an instrumental variable method that utilizes genetic information to investigate the causal effect of a modifiable exposure on an outcome. In most cases,…
A frequentist test of proportional colocalization after selecting relevant genetic variants
Ashish Patel, John C. Whittaker, Stephen Burgess
Colocalization analyses assess whether two traits are affected by the same or distinct causal genetic variants in a single gene region. A class of Bayesian colocalization tests are…
Disentangling the effects of traits with shared clustered genetic predictors using multivariable Mendelian randomization
Fatima Batool, Ashish Patel, Dipender Gill +1
When genetic variants in a gene cluster are associated with a disease outcome, the causal pathway from the variants to the outcome can be difficult to disentangle. For example, the…
Selecting invalid instruments to improve Mendelian randomization with two-sample summary data
Ashish Patel, Francis J. DiTraglia, Verena Zuber +1
Mendelian randomization (MR) is a widely-used method to estimate the causal relationship between a risk factor and disease. A fundamental part of any MR analysis is to choose appro…
Conditional inference in cis-Mendelian randomization using weak genetic factors
Ashish Patel, Dipender Gill, Paul J. Newcombe +1
Mendelian randomization is a widely-used method to estimate the unconfounded effect of an exposure on an outcome by using genetic variants as instrumental variables. Mendelian rand…
Two-Stage Penalized Regression Screening to Detect Biomarker-Treatment Interactions in Randomized Clinical Trials
Jixiong Wang, Ashish Patel, James M. S. Wason +1
High-dimensional biomarkers such as genomics are increasingly being measured in randomized clinical trials. Consequently, there is a growing interest in developing methods that imp…