2 citations · 4 across the 4 of their papers we have counts for
4 papers
Mendelian Randomization with Incomplete Exposure Data: a Bayesian Approach
Teresa Fazia, Leonardo Egidi, Burcu Ayoglu +9
We expand Mendelian Randomization (MR) methodology to deal with randomly missing data on either the exposure or the outcome variable, and furthermore with data from nonindependent…
Bayesian Mendelian Randomization identifies disease causing proteins via pedigree data, partially observed exposures and correlated instruments
Teresa Fazia, Leonardo Egidi, Burcu Ayoglu +7
Background In a study performed on multiplex Multiple Sclerosis (MS) Sardinian families to identify disease causing plasma proteins, application of Mendelian Randomization (MR) met…
Bayesian Mendelian Randomization
Carlo Berzuini, Hui Guo, Stephen Burgess +1
Our Bayesian approach to Mendelian Randomisation uses multiple instruments to assess the putative causal effect of an exposure on an outcome. The approach is robust to violations o…
Direct genetic effects and their estimation from matched case-control data
Carlo Berzuini, Stijn Vansteelandt, Luisa Foco +2
In genetic association studies, a single marker is often associated with multiple, correlated phenotypes (e.g., obesity and cardiovascular disease, or nicotine dependence and lung…