activity
20202026
most citedAverage causal effect estimation via instrumental variables: the no simultaneous heterogeneity assumption

11 citations · 11 across the 4 of their papers we have counts for

collaborators

5 papers

stat.ME2026

Towards more plausible point-identifying assumptions in two-sample Mendelian randomization

Fernando Pires Hartwig, Neil Martin Davies, George Davey Smith

Two-sample Mendelian randomization (MR) is a widely applied methodology in epidemiology. In two-sample MR, summary data (typically, regression coefficients and standard errors) qua…

stat.AP2021

How to estimate heritability, a guide for epidemiologists

Ciarrah-Jane S Barry, Venexia M Walker, Rosa C G Cheesman +3

Traditionally, heritability has been estimated using family-based methods such as twin studies. Advancements in molecular genomics have facilitated the development of alternative m…

q-fin.ST2021

The USS Trustee's risky strategy

Neil M Davies, Jackie Grant, Chin Yang Shapland

How much risk, and what types of risk, is the Universities Superannuation Scheme (USS) taking? This is a critical question for universities across the UK and many of their employee…

stat.ME2021

Homogeneity in the instrument-treatment association is not sufficient for the Wald estimand to equal the average causal effect for a binary instrument and a continuous exposure

Fernando Pires Hartwig, Linbo Wang, George Davey Smith +1

Background: Interpreting instrumental variable results often requires further assumptions in addition to the core assumptions of relevance, independence, and the exclusion restrict…

stat.ME2020★ 11 cited

Average causal effect estimation via instrumental variables: the no simultaneous heterogeneity assumption

F. P. Hartwig, L. Wang, G. Davey Smith +1

Background: Instrumental variables (IVs) can be used to provide evidence as to whether a treatment X has a causal effect on an outcome Y. Even if the instrument Z satisfies the thr…